Sebastian Pokutta

My group is interested in Artificial Intelligence, Optimization, and Machine Learning. We develop new methodologies (e.g., new optimization and learning algorithms), work on combining learning and decision-making, as well as design AI Systems for real-world deployment in various application contexts.

📬 Contact

office: Room 3026 at ZIB
Room MA MA606 at TUB
e-mail: pokutta (at) zib.de
pokutta (at) math.tu-berlin.de
homepage: pokutta.com

🎓 Curriculum vitae

since 2019: Professor at TUB
since 2019: Department Head at ZIB
since 2019: Vice President at ZIB
2005: Ph.D. in Mathematics at DUE
2003: Diploma in Mathematics at DUE

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📝 Publications and preprints

Preprints

Designolle, S., Vértesi, T., and Pokutta, S. (2024). Better Bounds on Grothendieck Constants of Finite Orders. [arXiv]

[BibTeX]

@misc{2023_DesignolleVertesiPokutta_Grothendieckconstants,
  archiveprefix = {arXiv},
  eprint = {2409.03739},
  primaryclass = {math.OC},
  year = {2024},
  author = {Designolle, Sébastien and Vértesi, Tamás and Pokutta, Sebastian},
  title = {Better Bounds on Grothendieck Constants of Finite Orders}
}

Göß, A., Martin, A., Pokutta, S., and Sharma, K. (2024). Norm-induced Cuts: Optimization with Lipschitzian Black-box Functions. [URL] [arXiv]

[BibTeX]

@misc{2024_AdrianMartinPokuttaSharma_Norminducedcuts,
  url = {https://opus4.kobv.de/opus4-trr154/files/518/nic_preprint.pdf},
  archiveprefix = {arXiv},
  eprint = {2403.11546},
  primaryclass = {math.OC},
  year = {2024},
  author = {Göß, Adrian and Martin, Alexander and Pokutta, Sebastian and Sharma, Kartikey},
  title = {Norm-induced Cuts: Optimization with Lipschitzian Black-box Functions}
}

Braun, G., Pokutta, S., and Woodstock, Z. (2024). Flexible Block-iterative Analysis for the Frank-Wolfe Algorithm. [arXiv]

[BibTeX]

@misc{2024_BraunPokuttaWoodstock_Blockiterativeanalysis,
  archiveprefix = {arXiv},
  eprint = {2409.06931},
  primaryclass = {math.OC},
  year = {2024},
  author = {Braun, Gábor and Pokutta, Sebastian and Woodstock, Zev},
  title = {Flexible Block-iterative Analysis for the Frank-Wolfe Algorithm}
}

Głuch, G., Turan, B., Nagarajan, S. G., and Pokutta, S. (2024). The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses. [arXiv]

[BibTeX]

@misc{2024_GrzegorzTuranNagarajanPokutta_Watermarksadversarialdefenses,
  archiveprefix = {arXiv},
  eprint = {2410.08864},
  primaryclass = {cs.LG},
  year = {2024},
  author = {Głuch, Grzegorz and Turan, Berkant and Nagarajan, Sai Ganesh and Pokutta, Sebastian},
  title = {The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses}
}

Mundinger, K., Zimmer, M., and Pokutta, S. (2024). Neural Parameter Regression for Explicit Representations of PDE Solution Operators. [arXiv]

[BibTeX]

@misc{2024_MundingerZimmerPokutta_Neuralparameterregression,
  archiveprefix = {arXiv},
  eprint = {2403.12764},
  primaryclass = {cs.LG},
  year = {2024},
  author = {Mundinger, Konrad and Zimmer, Max and Pokutta, Sebastian},
  title = {Neural Parameter Regression for Explicit Representations of PDE Solution Operators}
}

Haase, J., and Pokutta, S. (2024). Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration. [arXiv]

[BibTeX]

@misc{2024_Pokutta_HumanAICOcreative,
  archiveprefix = {arXiv},
  eprint = {2411.12527},
  primaryclass = {cs.HC},
  year = {2024},
  author = {Haase, Jennifer and Pokutta, Sebastian},
  title = {Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration}
}

Roux, C., Zimmer, M., and Pokutta, S. (2024). On the Byzantine-resilience of Distillation-based Federated Learning. [arXiv]

[BibTeX]

@misc{2024_RouxZimmerPokutta_Byzantineresilience,
  archiveprefix = {arXiv},
  eprint = {2402.12265},
  primaryclass = {cs.LG},
  year = {2024},
  author = {Roux, Christophe and Zimmer, Max and Pokutta, Sebastian},
  title = {On the Byzantine-resilience of Distillation-based Federated Learning}
}

Sadiku, S., Wagner, M., Nagarajan, S. G., and Pokutta, S. (2024). S-CFE: Simple Counterfactual Explanations. [arXiv]

[BibTeX]

@misc{2024_SadikuEtAl_Counterfactualexplanations,
  archiveprefix = {arXiv},
  eprint = {2410.15723},
  primaryclass = {cs.LG},
  year = {2024},
  author = {Sadiku, Shpresim and Wagner, Moritz and Nagarajan, Sai Ganesh and Pokutta, Sebastian},
  title = {S-CFE: Simple Counterfactual Explanations}
}

Wirth, E., Besançon, M., and Pokutta, S. (2024). The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control. [arXiv]

[BibTeX]

@misc{2024_WirthBesanconPokutta_Pivotingframework,
  archiveprefix = {arXiv},
  eprint = {2407.11760},
  primaryclass = {math.OC},
  year = {2024},
  author = {Wirth, Elias and Besançon, Mathieu and Pokutta, Sebastian},
  title = {The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control}
}

Wirth, E., Pena, J., and Pokutta, S. (2024). Fast Convergence of Frank-Wolfe Algorithms on Polytopes. [arXiv]

[BibTeX]

@misc{2024_WirthJavierPokutta_Frankwolfeconvergence,
  archiveprefix = {arXiv},
  eprint = {2406.18789},
  primaryclass = {math.OC},
  year = {2024},
  author = {Wirth, Elias and Pena, Javier and Pokutta, Sebastian},
  title = {Fast Convergence of Frank-Wolfe Algorithms on Polytopes}
}

Kerdreux, T., Scieur, D., d’Aspremont, A., and Pokutta, S. (2023). Strong Convexity of Feasible Sets in Riemannian Manifolds. [arXiv]

[BibTeX]

@misc{2022_KerdreuxScieurDaspremontPokutta_StrongconvexityRiemannianmanifolds,
  archiveprefix = {arXiv},
  eprint = {2312.03583},
  primaryclass = {math.OC},
  year = {2023},
  author = {Kerdreux, Thomas and Scieur, Damien and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Strong Convexity of Feasible Sets in Riemannian Manifolds}
}

Martínez-Rubio, D., Roux, C., Criscitiello, C., and Pokutta, S. (2023). Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. [arXiv]

[BibTeX]

@misc{2023_MartinezrubioRouxCriscitielloPokutta_Riemannianminmax,
  archiveprefix = {arXiv},
  eprint = {2305.16186},
  primaryclass = {math.OC},
  year = {2023},
  author = {Martínez-Rubio, David and Roux, Christophe and Criscitiello, Christopher and Pokutta, Sebastian},
  title = {Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties}
}

Sadiku, S., Wagner, M., and Pokutta, S. (2023). Group-wise Sparse and Explainable Adversarial Attacks. [arXiv]

[BibTeX]

@misc{2023_SadikuWagnerPokutta_Groupwisesparseattacks,
  archiveprefix = {arXiv},
  eprint = {2311.17434},
  primaryclass = {cs.CV},
  year = {2023},
  author = {Sadiku, Shpresim and Wagner, Moritz and Pokutta, Sebastian},
  title = {Group-wise Sparse and Explainable Adversarial Attacks}
}

Scieur, D., Kerdreux, T., Martínez-Rubio, D., d’Aspremont, A., and Pokutta, S. (2023). Strong Convexity of Sets in Riemannian Manifolds. [arXiv]

[BibTeX]

@misc{2023_ScieurEtAl_StrongconvexityRiemannianmanifolds,
  archiveprefix = {arXiv},
  eprint = {2312.03583},
  primaryclass = {math.OC},
  year = {2023},
  author = {Scieur, Damien and Kerdreux, Thomas and Martínez-Rubio, David and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Strong Convexity of Sets in Riemannian Manifolds}
}

Wirth, E., Pena, J., and Pokutta, S. (2023). Accelerated Affine-invariant Convergence Rates of the Frank-Wolfe Algorithm with Open-loop Step-sizes. [arXiv]

[BibTeX]

@misc{2023_WirthJavierPokutta_Affineinvariantconvergence,
  archiveprefix = {arXiv},
  eprint = {2310.04096},
  primaryclass = {math.OC},
  year = {2023},
  author = {Wirth, Elias and Pena, Javier and Pokutta, Sebastian},
  title = {Accelerated Affine-invariant Convergence Rates of the Frank-Wolfe Algorithm with Open-loop Step-sizes}
}

Woodstock, Z., and Pokutta, S. (2023). Splitting the Conditional Gradient Algorithm. [arXiv]

[BibTeX]

@misc{2023_WoodstockPokutta_Conditionalgradientnonconvex,
  archiveprefix = {arXiv},
  eprint = {2311.05381},
  primaryclass = {math.OC},
  year = {2023},
  author = {Woodstock, Zev and Pokutta, Sebastian},
  title = {Splitting the Conditional Gradient Algorithm}
}

Zimmer, M., Andoni, M., Spiegel, C., and Pokutta, S. (2023). PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs. [arXiv] [code]

[BibTeX]

@misc{2023_ZimmerAndoniSpiegelPokutta_PerpPruneRetrain,
  archiveprefix = {arXiv},
  eprint = {2312.15230},
  primaryclass = {cs.CL},
  year = {2023},
  author = {Zimmer, Max and Andoni, Megi and Spiegel, Christoph and Pokutta, Sebastian},
  title = {PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs},
  code = {https://github.com/ZIB-IOL/PERP}
}

Braun, G., Carderera, A., Combettes, C., Hassani, H., Karbasi, A., Mokhtari, A., and Pokutta, S. (2022). Conditional Gradient Methods. [arXiv]

[BibTeX]

@misc{2022_BraunEtAl_Conditionalgradient,
  archiveprefix = {arXiv},
  eprint = {2211.14103},
  primaryclass = {math.OC},
  year = {2022},
  author = {Braun, Gábor and Carderera, Alejandro and Combettes, Cyrille and Hassani, Hamed and Karbasi, Amin and Mokhtari, Aryan and Pokutta, Sebastian},
  title = {Conditional Gradient Methods}
}

Braun, G., Pokutta, S., and Weismantel, R. (2022). Alternating Linear Minimization: Revisiting von Neumann’s Alternating Projections. [arXiv] [slides] [video]

[BibTeX]

@misc{2022_BraunPokuttaWeismantel_Alternatingminimization,
  archiveprefix = {arXiv},
  eprint = {2212.02933},
  primaryclass = {math.OC},
  year = {2022},
  author = {Braun, Gábor and Pokutta, Sebastian and Weismantel, Robert},
  title = {Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections},
  slides = {https://pokutta.com/slides/20230327-icerm.pdf},
  video = {https://icerm.brown.edu/programs/sp-s23/w2/#schedule-item-4945}
}

Gelß, P., Klus, S., Knebel, S., Shakibaei, Z., and Pokutta, S. (2022). Low-rank Tensor Decompositions of Quantum Circuits. [arXiv]

[BibTeX]

@misc{2022_GelssKlusShakibaeiPokutta_Lowranktensordecompositions,
  archiveprefix = {arXiv},
  eprint = {2205.09882},
  primaryclass = {quant-ph},
  year = {2022},
  author = {Gelß, Patrick and Klus, Stefan and Knebel, Sebastian and Shakibaei, Zarin and Pokutta, Sebastian},
  title = {Low-rank Tensor Decompositions of Quantum Circuits}
}

Hendrych, D., Troppens, H., Besançon, M., and Pokutta, S. (2022). Convex Integer Optimization with Frank-Wolfe Methods. [arXiv] [slides] [code]

[BibTeX]

@misc{2022_HendrychTroppensBesanconPokutta_Convexintegerfrankwolfe,
  archiveprefix = {arXiv},
  eprint = {2208.11010},
  primaryclass = {math.OC},
  year = {2022},
  author = {Hendrych, Deborah and Troppens, Hannah and Besançon, Mathieu and Pokutta, Sebastian},
  title = {Convex Integer Optimization with Frank-Wolfe Methods},
  code = {https://github.com/ZIB-IOL/Boscia.jl},
  slides = {https://pokutta.com/slides/20220915_boscia.pdf}
}

Zimmer, M., Spiegel, C., and Pokutta, S. (2022). Compression-aware Training of Neural Networks Using Frank-Wolfe. [arXiv]

[BibTeX]

@misc{2022_ZimmerSpiegelPokutta_Compressionawaretraining,
  archiveprefix = {arXiv},
  eprint = {2205.11921},
  primaryclass = {cs.LG},
  year = {2022},
  author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian},
  title = {Compression-aware Training of Neural Networks Using Frank-Wolfe}
}

Braun, G., and Pokutta, S. (2021). Dual Prices for Frank–Wolfe Algorithms. [arXiv]

[BibTeX]

@misc{2021_BraunPokutta_DualpricesFrankwolfe,
  archiveprefix = {arXiv},
  eprint = {2101.02087},
  primaryclass = {math.OC},
  year = {2021},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {Dual Prices for Frank–Wolfe Algorithms}
}

Carderera, A., Pokutta, S., Schütte, C., and Weiser, M. (2021). CINDy: Conditional Gradient-based Identification of Non-linear Dynamics – Noise-robust Recovery. [arXiv]

[BibTeX]

@misc{2021_CardereraPokuttaSchutteWeiser_CINDy,
  archiveprefix = {arXiv},
  eprint = {2101.02630},
  primaryclass = {math.DS},
  year = {2021},
  author = {Carderera, Alejandro and Pokutta, Sebastian and Schütte, Christof and Weiser, Martin},
  title = {CINDy: Conditional Gradient-based Identification of Non-linear Dynamics -- Noise-robust Recovery}
}

Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2021). Local and Global Uniform Convexity Conditions. [arXiv]

[BibTeX]

@misc{2021_KerdrexDaspremontPokutta_LocalGlobalUniform,
  archiveprefix = {arXiv},
  eprint = {2102.05134},
  primaryclass = {math.OC},
  year = {2021},
  author = {Kerdreux, Thomas and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Local and Global Uniform Convexity Conditions}
}

Pokutta, S., and Xu, H. (2021). Adversaries in Online Learning Revisited: with Applications in Robust Optimization and Adversarial Training. [arXiv]

[BibTeX]

@misc{2021_PokuttaXu_AdversariesOnlineLearning,
  archiveprefix = {arXiv},
  eprint = {2101.11443},
  primaryclass = {cs.LG},
  year = {2021},
  author = {Pokutta, Sebastian and Xu, Huan},
  title = {Adversaries in Online Learning Revisited: with Applications in Robust Optimization and Adversarial Training}
}

Roux, C., Wirth, E., Pokutta, S., and Kerdreux, T. (2021). Efficient Online-bandit Strategies for Minimax Learning Problems. [arXiv]

[BibTeX]

@misc{2021_RouxWirthPokuttaKerdreux_Onlinebanditminimax,
  archiveprefix = {arXiv},
  eprint = {2105.13939},
  primaryclass = {cs.LG},
  year = {2021},
  author = {Roux, Christophe and Wirth, Elias and Pokutta, Sebastian and Kerdreux, Thomas},
  title = {Efficient Online-bandit Strategies for Minimax Learning Problems}
}

Carderera, A., and Pokutta, S. (2020). Second-order Conditional Gradient Sliding. [arXiv] [code]

[BibTeX]

@misc{2020_CarderaPokutta_SecondOrderConditional,
  archiveprefix = {arXiv},
  eprint = {2002.08907},
  primaryclass = {math.OC},
  year = {2020},
  author = {Carderera, Alejandro and Pokutta, Sebastian},
  title = {Second-order Conditional Gradient Sliding},
  code = {https://github.com/pokutta/Second-order-Conditional-Gradients}
}

Combettes, C., Spiegel, C., and Pokutta, S. (2020). Projection-free Adaptive Gradients for Large-scale Optimization. [arXiv] [summary] [code]

[BibTeX]

@misc{2020_CombettesSpiegelPokutta_Projectionfreeadaptivegradients,
  archiveprefix = {arXiv},
  eprint = {2009.14114},
  primaryclass = {math.OC},
  year = {2020},
  author = {Combettes, Cyrille and Spiegel, Christoph and Pokutta, Sebastian},
  title = {Projection-free Adaptive Gradients for Large-scale Optimization},
  code = {https://github.com/ZIB-IOL/StochasticFrankWolfe},
  summary = {https://pokutta.com/blog/research/2020/10/21/adasfw.html}
}

Pokutta, S., Spiegel, C., and Zimmer, M. (2020). Deep Neural Network Training with Frank-Wolfe. [arXiv] [summary] [code]

[BibTeX]

@misc{2020_PokuttaSpiegelZimmer_Frankwolfeneuralnetworks,
  archiveprefix = {arXiv},
  eprint = {2010.07243},
  primaryclass = {cs.LG},
  year = {2020},
  author = {Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
  title = {Deep Neural Network Training with Frank-Wolfe},
  code = {https://github.com/ZIB-IOL/StochasticFrankWolfe},
  summary = {https://pokutta.com/blog/research/2020/11/11/NNFW.html}
}

Braun, G., and Pokutta, S. (2016). An Efficient High-probability Algorithm for Linear Bandits. [arXiv]

[BibTeX]

@misc{2016_BraunPokutta_Highprobabilitylinearbandits,
  archiveprefix = {arXiv},
  eprint = {1610.02072},
  primaryclass = {cs.DS},
  year = {2016},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {An Efficient High-probability Algorithm for Linear Bandits}
}

Braun, G., and Pokutta, S. (2015). An Information Diffusion Fano Inequality. [arXiv]

[BibTeX]

@misc{2015_BraunPokutta_Informationdiffusionfano,
  archiveprefix = {arXiv},
  eprint = {1504.05492},
  primaryclass = {cs.IT},
  year = {2015},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {An Information Diffusion Fano Inequality}
}

Braun, G., and Pokutta, S. (2009). A Polyhedral Approach to Computing Border Bases. [arXiv]

[BibTeX]

@misc{2010_BraunPokutta_PolyhedralApproach,
  archiveprefix = {arXiv},
  eprint = {0911.0859},
  primaryclass = {math.AC},
  year = {2009},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {A Polyhedral Approach to Computing Border Bases}
}

Martin, A., Müller, J., and Pokutta, S. On Clearing Coupled Day-ahead Electricity Markets. [URL]

[BibTeX]

@misc{2010_MartinMullerPokutta_OnClearing,
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1660528},
  author = {Martin, Alexander and Müller, Johannes and Pokutta, Sebastian},
  title = {On Clearing Coupled Day-ahead Electricity Markets}
}

Pokutta, S., and Schulz, A. S. On the Rank of Cutting-plane Proof Systems. [URL]

[BibTeX]

@misc{2013_PokuttaSchulz_RankCuttingPlane,
  url = {https://optimization-online.org/2013/02/3782},
  author = {Pokutta, Sebastian and Schulz, Andreas S.},
  title = {On the Rank of Cutting-plane Proof Systems}
}

Conference proceedings

Wäldchen, S., Sharma, K., Turan, B., Zimmer, M., and Pokutta, S. (2024). Interpretability Guarantees with Merlin-Arthur Classifiers. Proceedings of the International Conference on Artificial Intelligence and Statistics. [arXiv]

[BibTeX]

@inproceedings{2022_WaeldchenEtAl_Interpretabilityguarantees,
  year = {2024},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  archiveprefix = {arXiv},
  eprint = {2206.00759},
  primaryclass = {cs.LG},
  author = {Wäldchen, Stephan and Sharma, Kartikey and Turan, Berkant and Zimmer, Max and Pokutta, Sebastian},
  title = {Interpretability Guarantees with Merlin-Arthur Classifiers}
}

Hendrych, D., Besançon, M., and Pokutta, S. (2024). Solving the Optimal Experiment Design Problem with Mixed-integer Convex Methods. Proceedings of the Symposium on Experimental Algorithms. DOI: 10.4230/LIPIcs.SEA.2024.16 [arXiv] [code]

[BibTeX]

@inproceedings{2023_HendrychBesanconPokutta_Optimalexperimentdesign,
  year = {2024},
  booktitle = {Proceedings of the Symposium on Experimental Algorithms},
  doi = {10.4230/LIPIcs.SEA.2024.16},
  archiveprefix = {arXiv},
  eprint = {2312.11200},
  primaryclass = {math.OC},
  author = {Hendrych, Deborah and Besançon, Mathieu and Pokutta, Sebastian},
  title = {Solving the Optimal Experiment Design Problem with Mixed-integer Convex Methods},
  code = {https://github.com/ZIB-IOL/OptimalDesignWithBoscia}
}

Kiem, A., Pokutta, S., and Spiegel, C. (2024). The Four-color Ramsey Multiplicity of Triangles. Proceedings of the Discrete Mathematics Days. [URL] [arXiv] [code]

[BibTeX]

@inproceedings{2023_KiemPokuttaSpiegel_4colorramsey,
  year = {2024},
  booktitle = {Proceedings of the Discrete Mathematics Days},
  url = {https://dmd2024.web.uah.es/files/abstracts/paper_3.pdf},
  archiveprefix = {arXiv},
  eprint = {2312.08049},
  primaryclass = {math.CO},
  author = {Kiem, Aldo and Pokutta, Sebastian and Spiegel, Christoph},
  title = {The Four-color Ramsey Multiplicity of Triangles},
  code = {https://github.com/FordUniver/kps_trianglemult}
}

Zimmer, M., Spiegel, C., and Pokutta, S. (2024). Sparse Model Soups: A Recipe for Improved Pruning Via Model Averaging. Proceedings of the International Conference on Learning Representations. [URL] [arXiv]

[BibTeX]

@inproceedings{2023_ZimmerSpiegelPokutta_Sparsemodelsoups,
  year = {2024},
  booktitle = {Proceedings of the International Conference on Learning Representations},
  url = {https://iclr.cc/virtual/2024/poster/17433},
  archiveprefix = {arXiv},
  eprint = {2306.16788},
  primaryclass = {cs.LG},
  author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian},
  title = {Sparse Model Soups: A Recipe for Improved Pruning Via Model Averaging}
}

Kiem, A., Pokutta, S., and Spiegel, C. (2024). Categorification of Flag Algebras. Proceedings of the Discrete Mathematics Days. [URL]

[BibTeX]

@inproceedings{2024_KiemPokuttaSpiegel_Categorificationflagalgebras,
  year = {2024},
  booktitle = {Proceedings of the Discrete Mathematics Days},
  url = {https://dmd2024.web.uah.es/files/abstracts/paper_47.pdf},
  author = {Kiem, Aldo and Pokutta, Sebastian and Spiegel, Christoph},
  title = {Categorification of Flag Algebras}
}

Martínez-Rubio, D., Roux, C., and Pokutta, S. (2024). Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point. Proceedings of the International Conference on Machine Learning. [URL] [arXiv]

[BibTeX]

@inproceedings{2024_MartinezrubioRouxPokutta_Riemanniangradientdescent,
  year = {2024},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  url = {https://proceedings.mlr.press/v235/marti-nez-rubio24a.html},
  archiveprefix = {arXiv},
  eprint = {2403.10429},
  primaryclass = {math.OC},
  author = {Martínez-Rubio, David and Roux, Christophe and Pokutta, Sebastian},
  title = {Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point}
}

Mundinger, K., Pokutta, S., Spiegel, C., and Zimmer, M. (2024). Extending the Continuum of Six-Colorings. Proceedings of the Discrete Mathematics Days. [URL] [arXiv]

[BibTeX]

@inproceedings{2024_MundingerPokuttaSpiegelZimmer_SixcoloringsExpansion:1,
  year = {2024},
  booktitle = {Proceedings of the Discrete Mathematics Days},
  url = {https://dmd2024.web.uah.es/files/abstracts/paper_27.pdf},
  archiveprefix = {arXiv},
  eprint = {2404.05509},
  primaryclass = {math.CO},
  author = {Mundinger, Konrad and Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
  title = {Extending the Continuum of Six-Colorings}
}

Pauls, J., Zimmer, M., Kelly, U. M., Schwartz, M., Saatchi, S., Ciais, P., Pokutta, S., Brandt, M., and Gieseke, F. (2024). Estimating Canopy Height at Scale. Proceedings of the International Conference on Machine Learning. [arXiv] [code]

[BibTeX]

@inproceedings{2024_PaulsEtAl_Canopyheightestimation,
  year = {2024},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  archiveprefix = {arXiv},
  eprint = {2406.01076},
  primaryclass = {cs.CV},
  author = {Pauls, Jan and Zimmer, Max and Kelly, Una M and Schwartz, Martin and Saatchi, Sassan and Ciais, Philippe and Pokutta, Sebastian and Brandt, Martin and Gieseke, Fabian},
  title = {Estimating Canopy Height at Scale},
  code = {https://github.com/AI4Forest/Global-Canopy-Height-Map}
}

Sharma, K., Hendrych, D., Besançon, M., and Pokutta, S. (2024). Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe. Proceedings of the INFORMS Optimization Society Conference. [arXiv]

[BibTeX]

@inproceedings{2024_SharmaHendrychBesanconPokutta_NetworkdesignMicoFrankwolfe,
  year = {2024},
  booktitle = {Proceedings of the INFORMS Optimization Society Conference},
  archiveprefix = {arXiv},
  eprint = {2402.00166},
  primaryclass = {math.OC},
  author = {Sharma, Kartikey and Hendrych, Deborah and Besançon, Mathieu and Pokutta, Sebastian},
  title = {Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe}
}

Zimmer, M., Spiegel, C., and Pokutta, S. (2023). How I Learned to Stop Worrying and Love Retraining. Proceedings of the International Conference on Learning Representations. [URL] [arXiv] [code]

[BibTeX]

@inproceedings{2021_ZimmerSpiegelPokutta_Retrainingpruning,
  year = {2023},
  booktitle = {Proceedings of the International Conference on Learning Representations},
  url = {https://iclr.cc/virtual/2023/poster/10914},
  archiveprefix = {arXiv},
  eprint = {2111.00843},
  primaryclass = {cs.LG},
  author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian},
  title = {How I Learned to Stop Worrying and Love Retraining},
  code = {https://github.com/ZIB-IOL/BIMP}
}

Martínez-Rubio, D., and Pokutta, S. (2023). Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. Proceedings of the Conference on Learning Theory. [URL] [arXiv] [poster]

[BibTeX]

@inproceedings{2022_MartinezrubioPokutta_Acceleratedriemannian,
  year = {2023},
  booktitle = {Proceedings of the Conference on Learning Theory},
  url = {https://proceedings.mlr.press/v195/martinez-rubio23a/martinez-rubio23a.pdf},
  archiveprefix = {arXiv},
  eprint = {2211.14645},
  primaryclass = {math.OC},
  author = {Martínez-Rubio, David and Pokutta, Sebastian},
  title = {Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties},
  poster = {https://pokutta.com/slides/20221203_poster_neurips_riemannian.pdf}
}

Parczyk, O., Pokutta, S., Spiegel, C., and Szabó, T. (2023). Fully Computer-assisted Proofs in Extremal Combinatorics. Proceedings of the AAAI Conference on Artificial Intelligence. DOI: 10.1609/aaai.v37i10.26470 [URL] [arXiv] [code]

[BibTeX]

@inproceedings{2022_ParczykPokuttaSpiegelSzabo_Ramseymultiplicityheuristics:1,
  year = {2023},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  doi = {10.1609/aaai.v37i10.26470},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26470},
  archiveprefix = {arXiv},
  eprint = {2206.04036},
  primaryclass = {math.CO},
  author = {Parczyk, Olaf and Pokutta, Sebastian and Spiegel, Christoph and Szabó, Tibor},
  title = {Fully Computer-assisted Proofs in Extremal Combinatorics},
  code = {https://zenodo.org/record/6602512#.YyvFhi8Rr5g}
}

Wirth, E., Kera, H., and Pokutta, S. (2023). Approximate Vanishing Ideal Computations at Scale. Proceedings of the International Conference on Learning Representations. [arXiv] [slides]

[BibTeX]

@inproceedings{2022_WirthKeraPokutta_Approximatevanishingideal,
  year = {2023},
  booktitle = {Proceedings of the International Conference on Learning Representations},
  archiveprefix = {arXiv},
  eprint = {2207.01236},
  primaryclass = {cs.LG},
  author = {Wirth, Elias and Kera, Hiroshi and Pokutta, Sebastian},
  title = {Approximate Vanishing Ideal Computations at Scale},
  slides = {https://pokutta.com/slides/20220915_avi_at_scale.pdf}
}

Wirth, E., Kerdreux, T., and Pokutta, S. (2023). Acceleration of Frank-Wolfe Algorithms with Open Loop Step-sizes. Proceedings of the International Conference on Artificial Intelligence and Statistics. [arXiv]

[BibTeX]

@inproceedings{2022_WirthKerdreuxPokutta_Frankwolfeacceleration,
  year = {2023},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  archiveprefix = {arXiv},
  eprint = {2205.12838},
  primaryclass = {math.OC},
  author = {Wirth, Elias and Kerdreux, Thomas and Pokutta, Sebastian},
  title = {Acceleration of Frank-Wolfe Algorithms with Open Loop Step-sizes}
}

Chmiela, A., Gleixner, A., Lichocki, P., and Pokutta, S. (2023). Online Learning for Scheduling MIP Heuristics. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 114–123. DOI: 10.1007/978-3-031-33271-5_8 [arXiv]

[BibTeX]

@inproceedings{2023_ChmielaGleixnerLichockiPokutta_Onlinelearningscheduling,
  year = {2023},
  booktitle = {Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research},
  pages = {114-123},
  doi = {10.1007/978-3-031-33271-5_8},
  archiveprefix = {arXiv},
  eprint = {2304.03755},
  primaryclass = {math.OC},
  author = {Chmiela, Antonia and Gleixner, Ambros and Lichocki, Pawel and Pokutta, Sebastian},
  title = {Online Learning for Scheduling MIP Heuristics}
}

Martínez-Rubio, D., Wirth, E., and Pokutta, S. (2023). Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond. Proceedings of the Conference on Learning Theory. [arXiv]

[BibTeX]

@inproceedings{2023_MartinezrubioWirthPokutta_Sparseapproximatepagerank,
  year = {2023},
  booktitle = {Proceedings of the Conference on Learning Theory},
  archiveprefix = {arXiv},
  eprint = {2303.12875},
  primaryclass = {math.OC},
  author = {Martínez-Rubio, David and Wirth, Elias and Pokutta, Sebastian},
  title = {Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond}
}

Thuerck, D., Sofranac, B., Pfetsch, M., and Pokutta, S. (2023). Learning Cuts Via Enumeration Oracles. Proceedings of the Conference on Neural Information Processing Systems. [arXiv]

[BibTeX]

@inproceedings{2023_ThuerckSofranacPfetschPokutta_Learningcutsenumeration,
  year = {2023},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  archiveprefix = {arXiv},
  eprint = {2305.12197},
  primaryclass = {math.OC},
  author = {Thuerck, Daniel and Sofranac, Boro and Pfetsch, Marc and Pokutta, Sebastian},
  title = {Learning Cuts Via Enumeration Oracles}
}

Gasse, M., Bowly, S., Cappart, Q., Charfreitag, J., Charlin, L., Chételat, D., Chmiela, A., Dumouchelle, J., Gleixner, A., Kazachkov, A. M., Khalil, E., Lichocki, P., Lodi, A., Lubin, M., Maddison, C. J., Christopher, M., Papageorgiou, D. J., Parjadis, A., Pokutta, S., … Kun, M. (2022). The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. Proceedings of the Conference on Neural Information Processing Systems, 176, 220–231. [URL] [arXiv]

[BibTeX]

@inproceedings{2022_GasseEtAl_Ml4coinsights,
  year = {2022},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  month = jun,
  volume = {176},
  pages = {220–231},
  url = {https://proceedings.mlr.press/v176/gasse22a.html},
  archiveprefix = {arXiv},
  eprint = {2203.02433},
  primaryclass = {cs.LG},
  author = {Gasse, Maxime and Bowly, Simon and Cappart, Quentin and Charfreitag, Jonas and Charlin, Laurent and Chételat, Didier and Chmiela, Antonia and Dumouchelle, Justin and Gleixner, Ambros and Kazachkov, Aleksandr M. and Khalil, Elias and Lichocki, Pawel and Lodi, Andrea and Lubin, Miles and Maddison, Chris J. and Christopher, Morris and Papageorgiou, Dimitri J. and Parjadis, Augustin and Pokutta, Sebastian and Prouvost, Antoine and Scavuzzo, Lara and Zarpellon, Giulia and Yang, Linxin and Lai, Sha and Wang, Akang and Luo, Xiaodong and Zhou, Xiang and Huang, Haohan and Shao, Shengcheng and Zhu, Yuanming and Zhang, Dong and Quan, Tao and Cao, Zixuan and Xu, Yang and Huang, Zhewei and Zhou, Shuchang and Binbin, Chen and Minggui, He and Hao, Hao and Zhiyu, Zhang and Zhiwu, An and Kun, Mao},
  title = {The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights}
}

Criado, F., Martínez-Rubio, D., and Pokutta, S. (2022). Fast Algorithms for Packing Proportional Fairness and Its Dual. Proceedings of the Conference on Neural Information Processing Systems. [arXiv] [poster]

[BibTeX]

@inproceedings{2021_CriadoMartinezrubioPokutta_Packingproportionalfairness,
  year = {2022},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  archiveprefix = {arXiv},
  eprint = {2109.03678},
  primaryclass = {math.OC},
  author = {Criado, Francisco and Martínez-Rubio, David and Pokutta, Sebastian},
  title = {Fast Algorithms for Packing Proportional Fairness and Its Dual},
  poster = {https://pokutta.com/slides/20211105_fairpacking-poster.pdf}
}

Macdonald, J., Besançon, M., and Pokutta, S. (2022). Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings. Proceedings of the International Conference on Machine Learning. [arXiv] [poster] [video]

[BibTeX]

@inproceedings{2021_MacdonaldBesanconPokutta_Interpretableneuralnetworks,
  year = {2022},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  archiveprefix = {arXiv},
  eprint = {2110.08105},
  primaryclass = {cs.LG},
  author = {Macdonald, Jan and Besançon, Mathieu and Pokutta, Sebastian},
  title = {Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings},
  poster = {https://pokutta.com/slides/20220712_icml_poster_interpretable_rde.pdf},
  video = {https://slideslive.com/38983588}
}

Tsuji, K., Tanaka, K., and Pokutta, S. (2022). Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding. Proceedings of the International Conference on Machine Learning. [arXiv] [summary] [slides] [code] [video]

[BibTeX]

@inproceedings{2021_TsujiTanakaPokutta_Pairwiseconditionalgradients,
  year = {2022},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  archiveprefix = {arXiv},
  eprint = {2110.12650},
  primaryclass = {cond-mat.quant-gas},
  author = {Tsuji, Kazuma and Tanaka, Ken'ichiro and Pokutta, Sebastian},
  title = {Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding},
  code = {https://github.com/ZIB-IOL/FrankWolfe.jl},
  slides = {https://pokutta.com/slides/20220624_ICML2022_BPCG.pdf},
  summary = {https://pokutta.com/blog/research/2022/05/21/bpcg-abstract.html},
  video = {https://slideslive.com/38983561}
}

Parczyk, O., Pokutta, S., Spiegel, C., and Szabó, T. (2022). New Ramsey Multiplicity Bounds and Search Heuristics. Proceedings of the Discrete Mathematics Days. [arXiv] [code]

[BibTeX]

@inproceedings{2022_ParczykPokuttaSpiegelSzabo_Ramseymultiplicityheuristics:2,
  year = {2022},
  booktitle = {Proceedings of the Discrete Mathematics Days},
  archiveprefix = {arXiv},
  eprint = {2206.04036},
  primaryclass = {math.CO},
  author = {Parczyk, Olaf and Pokutta, Sebastian and Spiegel, Christoph and Szabó, Tibor},
  title = {New Ramsey Multiplicity Bounds and Search Heuristics},
  code = {https://zenodo.org/record/6602512#.YyvFhi8Rr5g}
}

Wäldchen, S., Huber, F., and Pokutta, S. (2022). Training Characteristic Functions with Reinforcement Learning: XAI-methods Play Connect Four. Proceedings of the International Conference on Machine Learning. [arXiv] [poster] [video]

[BibTeX]

@inproceedings{2022_WaeldchenHuberPokutta_CharacteristicfunctionsReinforcementlearning,
  year = {2022},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  archiveprefix = {arXiv},
  eprint = {2202.11797},
  primaryclass = {cs.LG},
  author = {Wäldchen, Stephan and Huber, Felix and Pokutta, Sebastian},
  title = {Training Characteristic Functions with Reinforcement Learning: XAI-methods Play Connect Four},
  poster = {https://pokutta.com/slides/20220712_icml_poster_conn4.pdf},
  video = {https://slideslive.com/38983111}
}

Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Approximately Vanishing Ideal. Proceedings of the International Conference on Artificial Intelligence and Statistics. [arXiv] [summary] [poster] [code]

[BibTeX]

@inproceedings{2022_WirthPokutta_Conditionalgradients,
  year = {2022},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  archiveprefix = {arXiv},
  eprint = {2202.03349},
  primaryclass = {cs.LG},
  author = {Wirth, Elias and Pokutta, Sebastian},
  title = {Conditional Gradients for the Approximately Vanishing Ideal},
  code = {https://github.com/ZIB-IOL/cgavi/},
  poster = {https://pokutta.com/slides/20220223_CGAVI_poster.pdf},
  summary = {https://pokutta.com/blog/research/2022/02/20/CGAVI.html}
}

Carderera, A., Besançon, M., and Pokutta, S. (2021). Simple Steps Are All You Need: Frank-Wolfe and Generalized Self-concordant Functions. Proceedings of the Conference on Neural Information Processing Systems, 34, 5390–5401. [URL] [arXiv] [summary] [slides] [poster] [code]

[BibTeX]

@inproceedings{2024_CardereraBesanconPokutta_Scalablefrankwolfe:1,
  year = {2021},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  month = may,
  volume = {34},
  pages = {5390–5401},
  url = {https://proceedings.neurips.cc/paper_files/paper/2021/file/2b323d6eb28422cef49b266557dd31ad-Paper.pdf},
  archiveprefix = {arXiv},
  eprint = {2105.13913},
  primaryclass = {math.OC},
  author = {Carderera, Alejandro and Besançon, Mathieu and Pokutta, Sebastian},
  title = {Simple Steps Are All You Need: Frank-Wolfe and Generalized Self-concordant Functions},
  code = {https://doi.org/10.5281/zenodo.4836009},
  poster = {https://pokutta.com/slides/20211120_poster_NeurIPS21_lSimple_steps_are_all_you_need.pdf},
  slides = {https://pokutta.com/slides/20210710_FW-simpleSteps-SelfConcordance.pdf},
  summary = {https://pokutta.com/blog/research/2021/10/09/self-concordant-abstract.html}
}

Chmiela, A., Khalil, E. B., Gleixner, A., Lodi, A., and Pokutta, S. (2021). Learning to Schedule Heuristics in Branch-and-bound. Proceedings of the Conference on Neural Information Processing Systems, 34, 24235–24246. [URL] [arXiv] [poster]

[BibTeX]

@inproceedings{2021_ChmielaEtAl_Heuristicscheduling,
  year = {2021},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  month = mar,
  volume = {34},
  pages = {24235–24246},
  url = {https://proceedings.neurips.cc/paper_files/paper/2021/file/cb7c403aa312160380010ee3dd4bfc53-Paper.pdf},
  archiveprefix = {arXiv},
  eprint = {2103.10294},
  primaryclass = {cs.LG},
  author = {Chmiela, Antonia and Khalil, Elias B. and Gleixner, Ambros and Lodi, Andrea and Pokutta, Sebastian},
  title = {Learning to Schedule Heuristics in Branch-and-bound},
  poster = {https://pokutta.com/slides/20211120_poster_NeurIPS21_learningheuristics.pdf}
}

Carderera, A., Diakonikolas, J., Lin, C. Y., and Pokutta, S. (2021, February). Parameter-free Locally Accelerated Conditional Gradients. Proceedings of the International Conference on Machine Learning. [arXiv] [slides]

[BibTeX]

@inproceedings{2021_CardereraDiakonikolasLinPokutta_ParameterfreeLocallyAccelerated,
  year = {2021},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  month = feb,
  archiveprefix = {arXiv},
  eprint = {2102.06806},
  primaryclass = {math.OC},
  author = {Carderera, Alejandro and Diakonikolas, Jelena and Lin, Cheuk Yin and Pokutta, Sebastian},
  title = {Parameter-free Locally Accelerated Conditional Gradients},
  slides = {https://pokutta.com/slides/20210716_PF_LaCG_Poster.pdf}
}

Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2021, January). Projection-Free Optimization on Uniformly Convex Sets. Proceedings of the International Conference on Artificial Intelligence and Statistics. [arXiv] [slides]

[BibTeX]

@inproceedings{2021_KerdrexDaspremontPokutta_ProjectionFreeOptimization,
  year = {2021},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  month = jan,
  archiveprefix = {arXiv},
  eprint = {2004.11053},
  primaryclass = {math.OC},
  author = {Kerdreux, Thomas and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Projection-Free Optimization on Uniformly Convex Sets},
  slides = {https://app.box.com/s/36wj0o8le96rrfdxec774wk7rrdp2vlm}
}

Sofranac, B., Gleixner, A., and Pokutta, S. (2021). An Algorithm-independent Measure of Progress for Linear Constraint Propagation. Proceedings of the International Conference on Principles and Practice of Constraint Programming, 52:1–17. DOI: 10.4230/LIPIcs.CP.2021.52 [URL] [arXiv] [video]

[BibTeX]

@inproceedings{2021_SofranacGleixnerPokutta_Progressmeasure:1,
  year = {2021},
  booktitle = {Proceedings of the International Conference on Principles and Practice of Constraint Programming},
  pages = {52:1–17},
  doi = {10.4230/LIPIcs.CP.2021.52},
  url = {https://drops.dagstuhl.de/opus/volltexte/2021/15343/},
  archiveprefix = {arXiv},
  eprint = {2106.07573},
  primaryclass = {math.OC},
  author = {Sofranac, Boro and Gleixner, Ambros and Pokutta, Sebastian},
  title = {An Algorithm-independent Measure of Progress for Linear Constraint Propagation},
  video = {https://youtu.be/paZtGYlkBfE}
}

Pokutta, S. (2020, September). Restarting Algorithms: Sometimes There Is Free Lunch. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research. [arXiv] [slides] [video]

[BibTeX]

@inproceedings{2020_Pokutta_RestartingAlgorithms,
  year = {2020},
  booktitle = {Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research},
  month = sep,
  archiveprefix = {arXiv},
  eprint = {2006.14810},
  primaryclass = {math.OC},
  author = {Pokutta, Sebastian},
  title = {Restarting Algorithms: Sometimes There Is Free Lunch},
  slides = {https://app.box.com/s/8ps8bhjv2phhy182xn55iurk9t3o1xc3},
  video = {https://youtube.com/watch?v=v3Xzoda2_gQ}
}

Mortagy, H., Gupta, S., and Pokutta, S. (2020, June). Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization. Proceedings of the Conference on Neural Information Processing Systems. [arXiv] [slides] [code] [video]

[BibTeX]

@inproceedings{2020_MortagyGuptaPokutta_WalkingShadow,
  year = {2020},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  month = jun,
  archiveprefix = {arXiv},
  eprint = {2006.08426},
  primaryclass = {math.OC},
  author = {Mortagy, Hassan and Gupta, Swati and Pokutta, Sebastian},
  title = {Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization},
  code = {https://github.com/pokutta/Walking-in-the-Shadow},
  slides = {https://app.box.com/s/wjhpe4nh8kv5pw6vl5jbp902v3mksivs},
  video = {https://youtu.be/CRmASevfnmE}
}

Combettes, C., and Pokutta, S. (2020, March). Boosting Frank-Wolfe by Chasing Gradients. Proceedings of the International Conference on Machine Learning. [URL] [arXiv] [slides] [code] [video]

[BibTeX]

@inproceedings{2020_CombettesPokutta_BoostingFrankWolfe,
  year = {2020},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  month = mar,
  url = {https://proceedings.mlr.press/v119/combettes20a.html},
  archiveprefix = {arXiv},
  eprint = {2003.06369},
  primaryclass = {math.OC},
  author = {Combettes, Cyrille and Pokutta, Sebastian},
  title = {Boosting Frank-Wolfe by Chasing Gradients},
  code = {https://github.com/cyrillewcombettes/boostfw},
  slides = {https://app.box.com/s/wwj247r5d456q0778p9b9y1jm6txuifb},
  video = {https://youtube.com/watch?v=BfyV0C5FRbE}
}

Diakonikolas, J., Carderera, A., and Pokutta, S. (2020). Locally Accelerated Conditional Gradients. Proceedings of the International Conference on Artificial Intelligence and Statistics. [URL] [arXiv] [slides] [code]

[BibTeX]

@inproceedings{2019_DiakonikolasCardereraPokutta_BreakingCurse:1,
  year = {2020},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  url = {https://proceedings.mlr.press/v108/diakonikolas20a/diakonikolas20a.pdf},
  archiveprefix = {arXiv},
  eprint = {1906.07867},
  primaryclass = {math.OC},
  author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian},
  title = {Locally Accelerated Conditional Gradients},
  code = {https://colab.research.google.com/drive/1ejjfCan7xnEhWWJXCIzb03CwQRG9iW_O},
  slides = {https://app.box.com/s/gphkhapso7d1vrfnzqykkb3vx0agxh8w}
}

Pokutta, S., Singh, M., and Torrico Palacios, A. (2020). On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. Proceedings of the International Conference on Machine Learning. [arXiv] [slides] [video]

[BibTeX]

@inproceedings{2019_PokuttaSinghTorrico_UnreasonableEffectiveness:1,
  year = {2020},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  archiveprefix = {arXiv},
  eprint = {2002.04063},
  primaryclass = {cs.DS},
  author = {Pokutta, Sebastian and Singh, Mohit and Torrico Palacios, Alfredo},
  title = {On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness},
  slides = {https://app.box.com/s/fmjxhfdpiqubm28upf563ohy8t8fgl3a},
  video = {https://youtube.com/watch?v=VB1e0HrDmVo}
}

Pfetsch, M., and Pokutta, S. (2020). IPBoost – Non-Convex Boosting Via Integer Programming. Proceedings of the International Conference on Machine Learning. [arXiv] [slides] [code]

[BibTeX]

@inproceedings{2020_PfetschPokutta_IPBoost,
  year = {2020},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  archiveprefix = {arXiv},
  eprint = {2002.04679},
  primaryclass = {cs.LG},
  author = {Pfetsch, Marc and Pokutta, Sebastian},
  title = {IPBoost -- Non-Convex Boosting Via Integer Programming},
  code = {https://www2.mathematik.tu-darmstadt.de/~pfetsch/ipboost.html},
  slides = {https://app.box.com/s/8dpvmls88suouy11bkpwufhu7iiz6dxl}
}

Sofranac, B., Gleixner, A., and Pokutta, S. (2020). Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices. Proceedings of the 10th IEEE/ACM Workshop on Irregular Applications: Architectures and Algorithms, IA3 2020, 1–11. DOI: 10.1109/IA351965.2020.00007 [arXiv] [summary] [slides] [video]

[BibTeX]

@inproceedings{2020_SofranacGleixnerPokutta_Domainpropagation:1,
  year = {2020},
  booktitle = {Proceedings of the 10th IEEE/ACM Workshop on Irregular Applications: Architectures and Algorithms, IA3 2020},
  pages = {1-11},
  doi = {10.1109/IA351965.2020.00007},
  archiveprefix = {arXiv},
  eprint = {2009.07785},
  primaryclass = {cs.DC},
  author = {Sofranac, Boro and Gleixner, Ambros and Pokutta, Sebastian},
  title = {Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices},
  slides = {https://app.box.com/s/qy0pjmhtbm7shk2ypxjxlh2sj4nudvyu},
  summary = {https://pokutta.com/blog/research/2020/09/20/gpu-prob.html},
  video = {https://youtu.be/7mERPal9pVs}
}

Braun, G., Pokutta, S., Tu, D., and Wright, S. (2019). Blended Conditional Gradients: the Unconditioning of Conditional Gradients. Proceedings of the International Conference on Machine Learning, 97, 735–743. [URL] [arXiv] [summary] [slides] [poster] [code]

[BibTeX]

@inproceedings{2018_BraunPokuttaTuStephen_Blendedconditionalgradients,
  year = {2019},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  volume = {97},
  pages = {735–743},
  url = {https://proceedings.mlr.press/v97/braun19a},
  archiveprefix = {arXiv},
  eprint = {1805.07311},
  primaryclass = {math.OC},
  author = {Braun, Gábor and Pokutta, Sebastian and Tu, Dan and Wright, Stephen},
  title = {Blended Conditional Gradients: the Unconditioning of Conditional Gradients},
  code = {https://github.com/pokutta/bcg},
  poster = {https://app.box.com/s/nmmm671jd72i397nysa8emfnzh1hn6hf},
  slides = {https://app.box.com/s/xbx3z7ws6dxvl3rzgj4jp6forigycooe},
  summary = {https://pokutta.com/blog/research/2019/02/18/bcg-abstract.html}
}

Anari, N., Haghtalab, N., Naor, S., Pokutta, S., Singh, M., and Torrico Palacios, A. (2019). Structured Robust Submodular Maximization: Offline and Online Algorithms. Proceedings of the International Conference on Artificial Intelligence and Statistics. [URL] [arXiv]

[BibTeX]

@inproceedings{2019_AnariHaghtalabNaorPokuttaSinghTorrico_StructuredRobustSubmodular:1,
  year = {2019},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  url = {https://proceedings.mlr.press/v89/anari19a/anari19a.pdf},
  archiveprefix = {arXiv},
  eprint = {1710.04740},
  primaryclass = {cs.DS},
  author = {Anari, N. and Haghtalab, N. and Naor, S. and Pokutta, Sebastian and Singh, Mohit and Torrico Palacios, Alfredo},
  title = {Structured Robust Submodular Maximization: Offline and Online Algorithms}
}

Combettes, C., and Pokutta, S. (2019). Blended Matching Pursuit. Proceedings of the Conference on Neural Information Processing Systems. [URL] [arXiv] [slides] [code]

[BibTeX]

@inproceedings{2019_CombettesPokutta_BlendedMatching,
  year = {2019},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  url = {https://papers.nips.cc/paper/8478-blended-matching-pursuit},
  archiveprefix = {arXiv},
  eprint = {1904.12335},
  primaryclass = {math.OC},
  author = {Combettes, Cyrille and Pokutta, Sebastian},
  title = {Blended Matching Pursuit},
  code = {https://colab.research.google.com/drive/17XYIxnCcJjKswba9mAaXFWnNGVZdsaXQ},
  slides = {https://app.box.com/s/8lfktq6h3dqp9t2gqydu2tp8h2uxgz7m}
}

Diakonikolas, J., Carderera, A., and Pokutta, S. (2019). Breaking the Curse of Dimensionality (Locally) to Accelerate Conditional Gradients. Proceedings of the OPTML Workshop Paper. [URL] [arXiv] [slides] [code]

[BibTeX]

@inproceedings{2019_DiakonikolasCardereraPokutta_BreakingCurse,
  year = {2019},
  booktitle = {Proceedings of the OPTML Workshop Paper},
  url = {https://opt-ml.org/papers/2019/paper_26.pdf},
  archiveprefix = {arXiv},
  eprint = {1906.07867},
  primaryclass = {math.OC},
  author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian},
  title = {Breaking the Curse of Dimensionality (Locally) to Accelerate Conditional Gradients},
  code = {https://colab.research.google.com/drive/1ejjfCan7xnEhWWJXCIzb03CwQRG9iW_O},
  slides = {https://app.box.com/s/gphkhapso7d1vrfnzqykkb3vx0agxh8w}
}

Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2019). Restarting Frank-Wolfe. Proceedings of the International Conference on Artificial Intelligence and Statistics. [URL] [arXiv] [slides]

[BibTeX]

@inproceedings{2019_KerdrexDaspremontPokutta_RestartingFrankWolfe:1,
  year = {2019},
  booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
  url = {https://proceedings.mlr.press/v89/kerdreux19a/kerdreux19a.pdf},
  archiveprefix = {arXiv},
  eprint = {1810.02429},
  primaryclass = {math.OC},
  author = {Kerdreux, Thomas and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Restarting Frank-Wolfe},
  slides = {https://app.box.com/s/prd32r6xmuef2k4gah23rd0egllz9rv5}
}

Pokutta, S., Singh, M., and Torrico Palacios, A. (2019). On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. Proceedings of the OPTML Workshop Paper. [URL] [arXiv] [slides] [video]

[BibTeX]

@inproceedings{2019_PokuttaSinghTorrico_UnreasonableEffectiveness,
  year = {2019},
  booktitle = {Proceedings of the OPTML Workshop Paper},
  url = {https://opt-ml.org/papers/2019/paper_16.pdf},
  archiveprefix = {arXiv},
  eprint = {2002.04063},
  primaryclass = {cs.DS},
  author = {Pokutta, Sebastian and Singh, Mohit and Torrico Palacios, Alfredo},
  title = {On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness},
  slides = {https://app.box.com/s/fmjxhfdpiqubm28upf563ohy8t8fgl3a},
  video = {https://youtube.com/watch?v=VB1e0HrDmVo}
}

Inanlouganji, A., Pedrielli, G., Fainekos, G., and Pokutta, S. (2018). Continuous Simulation Optimization with Model Mismatch Using Gaussian Process Regression. Proceedings of the Proceedings of the 2018 Winter Simulation Conference.

[BibTeX]

@inproceedings{2018_InanlouganjiPedrielliFainekosPokutta_ContinuousSimulation,
  year = {2018},
  booktitle = {Proceedings of the Proceedings of the 2018 Winter Simulation Conference},
  author = {Inanlouganji, A. and Pedrielli, G. and Fainekos, G. and Pokutta, Sebastian},
  title = {Continuous Simulation Optimization with Model Mismatch Using Gaussian Process Regression}
}

Pokutta, S., Singh, M., and Torrico Palacios, A. (2018). Efficient Algorithms for Robust Submodular Maximization Under Matroid Constraints. Proceedings of the ICML Workshop Paper. [URL] [arXiv]

[BibTeX]

@inproceedings{2018_PokuttaSinghTorrico_EfficientAlgorithms,
  year = {2018},
  booktitle = {Proceedings of the ICML Workshop Paper},
  url = {https://sites.google.com/view/icml2018nonconvex/papers},
  archiveprefix = {arXiv},
  eprint = {1807.09405},
  primaryclass = {cs.DS},
  author = {Pokutta, Sebastian and Singh, Mohit and Torrico Palacios, Alfredo},
  title = {Efficient Algorithms for Robust Submodular Maximization Under Matroid Constraints}
}

Braun, G., Pokutta, S., and Zink, D. (2017). Lazifying Conditional Gradient Algorithms. Proceedings of the International Conference on Machine Learning, 70, 566–575. [URL] [arXiv] [slides] [poster]

[BibTeX]

@inproceedings{2016_BraunPokuttaZink_Lazifyinggradientalgorithms:1,
  year = {2017},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  volume = {70},
  pages = {566–575},
  url = {https://proceedings.mlr.press/v70/braun17a},
  archiveprefix = {arXiv},
  eprint = {1610.05120},
  primaryclass = {cs.DS},
  author = {Braun, Gábor and Pokutta, Sebastian and Zink, Daniel},
  title = {Lazifying Conditional Gradient Algorithms},
  poster = {https://app.box.com/s/lysscdg17ytpz7mqr0tu2djffyqvkl6a},
  slides = {https://app.box.com/s/zsp0hixjz2ha23u1vuyosijjkjdh8k}
}

Arumugam, K., Kadampot, I., Tahmasbi, M., Shah, S., Bloch, M., and Pokutta, S. (2017). Modulation Recognition Using Side Information and Hybrid Learning. Proceedings of the Proceedings of IEEE DySPAN.

[BibTeX]

@inproceedings{2017_ArumugamKadampotTahmasbiShahBlochPokutta_ModulationRecognition,
  year = {2017},
  booktitle = {Proceedings of the Proceedings of IEEE DySPAN},
  author = {Arumugam, K. and Kadampot, I. and Tahmasbi, M. and Shah, S. and Bloch, M. and Pokutta, Sebastian},
  title = {Modulation Recognition Using Side Information and Hybrid Learning}
}

Lan, G., Pokutta, S., Zhou, Y., and Zink, D. (2017). Conditional Accelerated Lazy Stochastic Gradient Descent. Proceedings of the International Conference on Machine Learning. [URL] [arXiv]

[BibTeX]

@inproceedings{2017_LanPokuttaZhouZink_ConditionalAccelerated,
  year = {2017},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  url = {https://proceedings.mlr.press/v70/lan17a.html},
  archiveprefix = {arXiv},
  eprint = {1703.05840},
  primaryclass = {cs.LG},
  author = {Lan, G. and Pokutta, Sebastian and Zhou, Y and Zink, Daniel},
  title = {Conditional Accelerated Lazy Stochastic Gradient Descent}
}

Roy, A., Xu, H., and Pokutta, S. (2017). Reinforcement Learning Under Model Mismatch. Proceedings of the Conference on Neural Information Processing Systems. [arXiv]

[BibTeX]

@inproceedings{2017_RoyXuPokutta_ReinforcementLearning,
  year = {2017},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  archiveprefix = {arXiv},
  eprint = {1706.04711},
  primaryclass = {cs.LG},
  author = {Roy, Aurko and Xu, Huan and Pokutta, Sebastian},
  title = {Reinforcement Learning Under Model Mismatch}
}

Bärmann, A., Pokutta, S., and Schneider, O. (2017). Emulating the Expert: Inverse Optimization Through Online Learning. Proceedings of the International Conference on Machine Learning. [URL] [arXiv] [slides] [video]

[BibTeX]

@inproceedings{2018_BarmannMartinPokuttaSchneider_OnlineLearningApproach,
  year = {2017},
  booktitle = {Proceedings of the International Conference on Machine Learning},
  url = {https://proceedings.mlr.press/v70/barmann17a.html},
  archiveprefix = {arXiv},
  eprint = {1810.12997},
  primaryclass = {math.OC},
  author = {Bärmann, Andreas and Pokutta, Sebastian and Schneider, Oskar},
  title = {Emulating the Expert: Inverse Optimization Through Online Learning},
  slides = {https://app.box.com/s/7ti8sz8mf5s2znn1qo32in4jxy5gjnn1},
  video = {https://vimeo.com/channels/1301905/237243668}
}

Braun, G., Pokutta, S., and Roy, A. (2016). Strong Reductions for Extended Formulations. Proceedings of the Conference on Integer Programming and Combinatorial Optimization, 9682, 350–361. DOI: 10.1007/978-3-319-33461-5_29 [arXiv]

[BibTeX]

@inproceedings{2015_BraunPokuttaRoy_Strongreductions:1,
  year = {2016},
  booktitle = {Proceedings of the Conference on Integer Programming and Combinatorial Optimization},
  month = jun,
  volume = {9682},
  pages = {350–361},
  doi = {10.1007/978-3-319-33461-5_29},
  archiveprefix = {arXiv},
  eprint = {1512.04932},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Pokutta, Sebastian and Roy, Aurko},
  title = {Strong Reductions for Extended Formulations}
}

Braun, G., Brown-Cohen, J., Huq, A., Pokutta, S., Raghavendra, P., Roy, A., Weitz, B., and Zink, D. (2016). The Matching Problem Has No Small Symmetric SDP. Proceedings of the Symposium on Discrete Algorithms, 1067–1078. DOI: 10.1137/1.9781611974331.ch75 [arXiv]

[BibTeX]

@inproceedings{2015_BraunEtAl_MatchingproblemSdp:1,
  year = {2016},
  booktitle = {Proceedings of the Symposium on Discrete Algorithms},
  pages = {1067–1078},
  doi = {10.1137/1.9781611974331.ch75},
  archiveprefix = {arXiv},
  eprint = {1504.00703},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Brown-Cohen, Jonah and Huq, Arefin and Pokutta, Sebastian and Raghavendra, Prasad and Roy, Aurko and Weitz, Benjamin and Zink, Daniel},
  title = {The Matching Problem Has No Small Symmetric SDP}
}

Roy, A., and Pokutta, S. (2016). Hierarchical Clustering Via Spreading Metrics. Proceedings of the Conference on Neural Information Processing Systems. [URL] [arXiv]

[BibTeX]

@inproceedings{2017_RoyPokutta_HierarchicalClustering:1,
  year = {2016},
  booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
  url = {https://papers.nips.cc/paper/by-source-2016-1199},
  archiveprefix = {arXiv},
  eprint = {1610.09269},
  primaryclass = {cs.LG},
  author = {Roy, Aurko and Pokutta, Sebastian},
  title = {Hierarchical Clustering Via Spreading Metrics}
}

Braun, G., Pokutta, S., and Zink, D. (2015). Inapproximability of Combinatorial Problems Via Small LPs and SDPs. Proceedings of the Annual Symposium on Theory of Computing, 107–116. DOI: 10.1145/2746539.2746550 [arXiv] [video]

[BibTeX]

@inproceedings{2014_BraunPokuttaZink_Affinereductions:1,
  year = {2015},
  booktitle = {Proceedings of the Annual Symposium on Theory of Computing},
  month = jun,
  pages = {107–116},
  doi = {10.1145/2746539.2746550},
  archiveprefix = {arXiv},
  eprint = {1410.8816},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Pokutta, Sebastian and Zink, Daniel},
  title = {Inapproximability of Combinatorial Problems Via Small LPs and SDPs},
  video = {https://youtu.be/MxLEticZ8RY}
}

Braun, G., and Pokutta, S. (2015). The Matching Polytope Does Not Admit Fully-polynomial Size Relaxation Schemes. Proceedings of the Symposium on Discrete Algorithms, 837–846. DOI: 10.1137/1.9781611973730.57 [arXiv]

[BibTeX]

@inproceedings{2014_BraunPokutta_Matchingpolytope,
  year = {2015},
  booktitle = {Proceedings of the Symposium on Discrete Algorithms},
  pages = {837-846},
  doi = {10.1137/1.9781611973730.57},
  archiveprefix = {arXiv},
  eprint = {1403.6710},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {The Matching Polytope Does Not Admit Fully-polynomial Size Relaxation Schemes}
}

Bazzi, A., Fiorini, S., Pokutta, S., and Svensson, O. (2015). Small Linear Programs Cannot Approximate Vertex Cover Within a Factor of 2 - Ε. Proceedings of the IEEE Symposium on Foundations of Computer Science. [arXiv] [slides]

[BibTeX]

@inproceedings{2015_BazziFioriniPokuttaSvensson_SmallLinearPrograms:1,
  year = {2015},
  booktitle = {Proceedings of the IEEE Symposium on Foundations of Computer Science},
  archiveprefix = {arXiv},
  eprint = {1503.00753},
  primaryclass = {cs.CC},
  author = {Bazzi, A. and Fiorini, S. and Pokutta, Sebastian and Svensson, O.},
  title = {Small Linear Programs Cannot Approximate Vertex Cover Within a Factor of 2 - Ε},
  slides = {https://app.box.com/s/00aqupo722bbpmdcyzwt8xmfqzyu14iy}
}

Collier, V., Ostrowski, J., and Pokutta, S. (2015). A Symmetric Extended Formulation of the Bin Packing Problem. Proceedings of the Proceedings of IIE Annual Conference.

[BibTeX]

@inproceedings{2015_CollierOstrowskiPokutta_SymmetricExtendedBin,
  year = {2015},
  booktitle = {Proceedings of the Proceedings of IIE Annual Conference},
  author = {Collier, V. and Ostrowski, J. and Pokutta, Sebastian},
  title = {A Symmetric Extended Formulation of the Bin Packing Problem}
}

Pokutta, S. (2015). Information Theory and Polyhedral Combinatorics. Proceedings of the Proceedings of 53rd Annual Allerton Conference on Communication, Control, and Computing. [URL]

[BibTeX]

@inproceedings{2015_Pokutta_InformationTheoryPolyhedral,
  year = {2015},
  booktitle = {Proceedings of the Proceedings of 53rd Annual Allerton Conference on Communication, Control, and Computing},
  url = {https://ieeexplore.ieee.org/abstract/document/7447134},
  author = {Pokutta, Sebastian},
  title = {Information Theory and Polyhedral Combinatorics}
}

Song, R., Xie, Y., and Pokutta, S. (2015). Sequential Sensing with Model Mismatch. Proceedings of the Proceedings of ISIT. [arXiv]

[BibTeX]

@inproceedings{2015_SongXiePokutta_SequentialSensing,
  year = {2015},
  booktitle = {Proceedings of the Proceedings of ISIT},
  archiveprefix = {arXiv},
  eprint = {1501.06241},
  primaryclass = {stat.ML},
  author = {Song, R. and Xie, Yao and Pokutta, Sebastian},
  title = {Sequential Sensing with Model Mismatch}
}

Xie, Y., Li, Q., and Pokutta, S. (2015). Supervised Online Subspace Tracking. Proceedings of the Proceedings of Asilomar Conference on Signals, Systems, and Computers.

[BibTeX]

@inproceedings{2015_XieLiPokutta_SupervisedOnlineSubspace,
  year = {2015},
  booktitle = {Proceedings of the Proceedings of Asilomar Conference on Signals, Systems, and Computers},
  author = {Xie, Yao and Li, Q. and Pokutta, Sebastian},
  title = {Supervised Online Subspace Tracking}
}

Braun, G., Firorini, S., and Pokutta, S. (2014). Average Case Polyhedral Complexity of the Maximum Stable Set Problem. Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 28, 515–530. DOI: 10.4230/LIPIcs.APPROX-RANDOM.2014.515 [URL] [arXiv]

[BibTeX]

@inproceedings{2013_BraunSamuelPokutta_Averagepolyhedralcomplexity:1,
  year = {2014},
  booktitle = {Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques},
  month = sep,
  volume = {28},
  pages = {515–530},
  doi = {10.4230/LIPIcs.APPROX-RANDOM.2014.515},
  url = {https://drops.dagstuhl.de/opus/volltexte/2014/4720},
  archiveprefix = {arXiv},
  eprint = {1311.4001},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Firorini, Samuel and Pokutta, Sebastian},
  title = {Average Case Polyhedral Complexity of the Maximum Stable Set Problem}
}

Braun, G., Pokutta, S., and Xie, Y. (2014). Info-greedy Sequential Adaptive Compressed Sensing. Proceedings of the Allerton Conference on Communication, Control, and Computing (Allerton), 858–865. DOI: 10.1109/ALLERTON.2014.7028544 [arXiv]

[BibTeX]

@inproceedings{2014_BraunPokuttaYao_Infogreedycompressedsensing:1,
  year = {2014},
  booktitle = {Proceedings of the Allerton Conference on Communication, Control, and Computing (Allerton)},
  pages = {858–865},
  doi = {10.1109/ALLERTON.2014.7028544},
  archiveprefix = {arXiv},
  eprint = {1407.0731},
  primaryclass = {cs.IT},
  author = {Braun, Gábor and Pokutta, Sebastian and Xie, Yao},
  title = {Info-greedy Sequential Adaptive Compressed Sensing}
}

Briet, J., Dadush, D., and Pokutta, S. (2013). On the Existence of 0/1 Polytopes with High Semidefinite Extension Complexity. Proceedings of the European Symposium on Algorithms. [arXiv]

[BibTeX]

@inproceedings{2013_BrietDadushPokutta_ExistencePolytopes:1,
  year = {2013},
  booktitle = {Proceedings of the European Symposium on Algorithms},
  archiveprefix = {arXiv},
  eprint = {1305.3268},
  primaryclass = {cs.CC},
  author = {Briet, Jop and Dadush, Daniel and Pokutta, Sebastian},
  title = {On the Existence of 0/1 Polytopes with High Semidefinite Extension Complexity}
}

Schmaltz, C., Pokutta, S., Heidorn, T., and Andrae, S. (2013). How to Make Regulators and Shareholders Happy Under Basel III. Proceedings of the Proceedings of the 26th Australasian Finance and Banking Conference. DOI: 10.1016/j.jbankfin.2014.05.031 [URL]

[BibTeX]

@inproceedings{2013_SchmaltzPokuttaHeidornAndrae_BaselIII:1,
  year = {2013},
  booktitle = {Proceedings of the Proceedings of the 26th Australasian Finance and Banking Conference},
  doi = {10.1016/j.jbankfin.2014.05.031},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2179490},
  author = {Schmaltz, Christian and Pokutta, Sebastian and Heidorn, Thomas and Andrae, Silvio},
  title = {How to Make Regulators and Shareholders Happy Under Basel III}
}

Braun, G., and Pokutta, S. (2013). Common Information and Unique Disjointness. Proceedings of the IEEE Symposium on Foundations of Computer Science, 688–697. [URL]

[BibTeX]

@inproceedings{2016_BraunPokutta_CommoninformationDisjointness:1,
  year = {2013},
  booktitle = {Proceedings of the IEEE Symposium on Foundations of Computer Science},
  pages = {688–697},
  url = {https://eccc.weizmann.ac.il/report/2013/056},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {Common Information and Unique Disjointness}
}

Braun, G., and Pokutta, S. (2012). An Algebraic Approach to Symmetric Extended Formulations. Proceedings of the International Symposium on Combinatorial Optimization, 7422, 141–152. DOI: 10.1007/978-3-642-32147-4_14 [arXiv]

[BibTeX]

@inproceedings{2012_BraunPokutta_Algebraicsymmetricformulations,
  year = {2012},
  booktitle = {Proceedings of the International Symposium on Combinatorial Optimization},
  month = apr,
  volume = {7422},
  pages = {141–152},
  doi = {10.1007/978-3-642-32147-4_14},
  archiveprefix = {arXiv},
  eprint = {1206.6318},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {An Algebraic Approach to Symmetric Extended Formulations}
}

Braun, G., Firorini, S., Pokutta, S., and Steurer, D. (2012). Approximation Limits of Linear Programs (beyond Hierarchies). Proceedings of the IEEE Symposium on Foundations of Computer Science, 480–489. DOI: 10.1109/FOCS.2012.10 [arXiv]

[BibTeX]

@inproceedings{2012_BraunSamuelPokuttaSteurer_Approximationlimits:1,
  year = {2012},
  booktitle = {Proceedings of the IEEE Symposium on Foundations of Computer Science},
  pages = {480–489},
  doi = {10.1109/FOCS.2012.10},
  archiveprefix = {arXiv},
  eprint = {1204.0957},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Firorini, Samuel and Pokutta, Sebastian and Steurer, David},
  title = {Approximation Limits of Linear Programs (beyond Hierarchies)}
}

Fiorini, S., Massar, S., Pokutta, S., Tiwary, H. R., and de Wolf, R. (2012). Linear Vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds. Proceedings of the Annual Symposium on Theory of Computing. [arXiv]

[BibTeX]

@inproceedings{2012_FioriniMassarPokuttaTiwaryWolf_LinearVsSemidefinite:1,
  year = {2012},
  booktitle = {Proceedings of the Annual Symposium on Theory of Computing},
  archiveprefix = {arXiv},
  eprint = {1111.0837},
  primaryclass = {math.CO},
  author = {Fiorini, S. and Massar, S. and Pokutta, Sebastian and Tiwary, H.R. and de Wolf, R.},
  title = {Linear Vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds}
}

Dey, S. S., and Pokutta, S. (2011). Design and Verify: a New Scheme for Generating Cutting-planes. Proceedings of the Conference on Integer Programming and Combinatorial Optimization, 6655, 143–155. DOI: 10.1007/978-3-642-20807-2_12 [URL]

[BibTeX]

@inproceedings{2011_DeyPokutta_DesignVerify:1,
  year = {2011},
  booktitle = {Proceedings of the Conference on Integer Programming and Combinatorial Optimization},
  volume = {6655},
  pages = {143-155},
  doi = {10.1007/978-3-642-20807-2_12},
  url = {https://optimization-online.org/2011/04/3002},
  author = {Dey, Santanu Sabush and Pokutta, Sebastian},
  title = {Design and Verify: a New Scheme for Generating Cutting-planes}
}

Helmke, H., Gluchshenko, O., Martin, A., Peter, A., Pokutta, S., and Siebert, U. (2011). Optimal Mixed-Mode Runway Scheduling. Proceedings of the Proceedings of DACS.

[BibTeX]

@inproceedings{2011_HelmkeGluchshenkoMartinPeterPokuttaSiebert_OptimalMixed,
  year = {2011},
  booktitle = {Proceedings of the Proceedings of DACS},
  author = {Helmke, H. and Gluchshenko, O. and Martin, Alexander and Peter, A. and Pokutta, Sebastian and Siebert, U.},
  title = {Optimal Mixed-Mode Runway Scheduling}
}

Pokutta, S., and Schmaltz, C. (2011). A Network Model for Bank Lending Capacity. Proceedings of the Proceedings of Systemic Risk, Basel III, Financial Stability and Regulation. [URL]

[BibTeX]

@inproceedings{2011_PokuttaSchmaltz_NetworkModel,
  year = {2011},
  booktitle = {Proceedings of the Proceedings of Systemic Risk, Basel III, Financial Stability and Regulation},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1773964},
  author = {Pokutta, Sebastian and Schmaltz, Christian},
  title = {A Network Model for Bank Lending Capacity}
}

Braun, G., and Pokutta, S. (2010). Rank of Random Half-integral Polytopes. Proceedings of the Electronic Notes in Discrete Mathematics, 36, 415–422. DOI: 10.1016/j.endm.2010.05.053 [URL]

[BibTeX]

@inproceedings{2011_BraunPokutta_Randomhalfintegralpolytopes:1,
  year = {2010},
  booktitle = {Proceedings of the Electronic Notes in Discrete Mathematics},
  month = aug,
  volume = {36},
  pages = {415–422},
  doi = {10.1016/j.endm.2010.05.053},
  url = {https://optimization-online.org/2010/11/2813},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {Rank of Random Half-integral Polytopes}
}

Pokutta, S., and Schulz, A. S. (2010). On the Rank of Generic Cutting-plane Proof Systems. Proceedings of the Conference on Integer Programming and Combinatorial Optimization, 6080, 450–463. DOI: 10.1007/978-3-642-13036-6_34 [URL]

[BibTeX]

@inproceedings{2010_PokuttaSchulz_RankGenericCutting,
  year = {2010},
  booktitle = {Proceedings of the Conference on Integer Programming and Combinatorial Optimization},
  volume = {6080},
  pages = {450-463},
  doi = {10.1007/978-3-642-13036-6_34},
  url = {https://optimization-online.org/2013/02/3782},
  author = {Pokutta, Sebastian and Schulz, Andreas S.},
  title = {On the Rank of Generic Cutting-plane Proof Systems}
}

Pokutta, S., and Schmaltz, C. (2009). Optimal Degree of Centralization of Liquidity Management. Proceedings of the Proceedings of 22nd Australasian Finance and Banking Conference. [URL]

[BibTeX]

@inproceedings{2009_PokuttaSchmaltz_OptimalDegreeCentralization,
  year = {2009},
  booktitle = {Proceedings of the Proceedings of 22nd Australasian Finance and Banking Conference},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1458963},
  author = {Pokutta, Sebastian and Schmaltz, Christian},
  title = {Optimal Degree of Centralization of Liquidity Management}
}

Alf, M., and Pokutta, S. (2006). How Logistics Service Providers Can Make Use of the Real Options Concept. Proceedings of the Symposium Mathematik & Logistik, Bad Honnef 2005, Conference Proceedings.

[BibTeX]

@inproceedings{2006_AlfPokutta_LogisticsServiceProviders,
  year = {2006},
  booktitle = {Proceedings of the Symposium Mathematik & Logistik, Bad Honnef 2005, Conference Proceedings},
  author = {Alf, M. and Pokutta, Sebastian},
  title = {How Logistics Service Providers Can Make Use of the Real Options Concept}
}

Full articles

Abbas, A., Ambainis, A., Augustino, B., Bärtschi, A., Buhrman, H., Coffrin, C., Cortiana, G., Dunjko, V., Egger, D. J., Elmegreen, B. G., Franco, N., Fratini, F., Fuller, B., Gacon, J., Gonciulea, C., Gribling, S., Gupta, S., Hadfield, S., Heese, R., … Zoufal, C. (2024). Challenges and Opportunities in Quantum Optimization. Nature Reviews Physics. DOI: https://doi.org/10.1038/s42254-024-00770-9 [arXiv]

[BibTeX]

@article{2023_AmiraEtAl_Quantumoptimization,
  year = {2024},
  journal = {Nature Reviews Physics},
  month = sep,
  doi = {https://doi.org/10.1038/s42254-024-00770-9},
  archiveprefix = {arXiv},
  eprint = {2312.02279},
  primaryclass = {quant-ph},
  author = {Abbas, Amira and Ambainis, Andris and Augustino, Brandon and Bärtschi, Andreas and Buhrman, Harry and Coffrin, Carleton and Cortiana, Giorgio and Dunjko, Vedran and Egger, Daniel J. and Elmegreen, Bruce G. and Franco, Nicola and Fratini, Filippo and Fuller, Bryce and Gacon, Julien and Gonciulea, Constantin and Gribling, Sander and Gupta, Swati and Hadfield, Stuart and Heese, Raoul and Kircher, Gerhard and Kleinert, Thomas and Koch, Thorsten and Korpas, Georgios and Lenk, Steve and Marecek, Jakub and Markov, Vanio and Mazzola, Guglielmo and Mensa, Stefano and Mohseni, Naeimeh and Nannicini, Giacomo and O'Meara, Corey and Peña Tapia, Elena and Pokutta, Sebastian and Proissl, Manuel and Rebentrost, Patrick and Sahin, Emre and Symons, Benjamin C. B. and Tornow, Sabine and Valls, Victor and Woerner, Stefan and Wolf-Bauwens, Mira L. and Yard, Jon and Yarkoni, Sheir and Zechiel, Dirk and Zhuk, Sergiy and Zoufal, Christa},
  title = {Challenges and Opportunities in Quantum Optimization}
}

Carderera, A., Besançon, M., and Pokutta, S. (2024). Scalable Frank-Wolfe on Generalized Self-concordant Functions Via Simple Steps. SIAM Journal on Optimization, 34(3), 2231–2258. DOI: 10.1137/23M1616789 [arXiv] [summary] [slides] [poster] [code]

[BibTeX]

@article{2024_CardereraBesanconPokutta_Scalablefrankwolfe,
  year = {2024},
  journal = {SIAM Journal on Optimization},
  month = sep,
  volume = {34},
  number = {3},
  pages = {2231-2258},
  doi = {10.1137/23M1616789},
  archiveprefix = {arXiv},
  eprint = {2105.13913},
  primaryclass = {math.OC},
  author = {Carderera, Alejandro and Besançon, Mathieu and Pokutta, Sebastian},
  title = {Scalable Frank-Wolfe on Generalized Self-concordant Functions Via Simple Steps},
  code = {https://doi.org/10.5281/zenodo.4836009},
  poster = {https://pokutta.com/slides/20211120_poster_NeurIPS21_lSimple_steps_are_all_you_need.pdf},
  slides = {https://pokutta.com/slides/20210710_FW-simpleSteps-SelfConcordance.pdf},
  summary = {https://pokutta.com/blog/research/2021/10/09/self-concordant-abstract.html}
}

Braun, G., Guzmán, C., and Pokutta, S. (2024). Corrections to “Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization Via Information Theory.” IEEE Transactions on Information Theory, 70, 5408–5409. DOI: 10.1109/TIT.2024.3357200

[BibTeX]

@article{2024_BraunGuzmanPokutta_Oraclecomplexity,
  year = {2024},
  journal = {IEEE Transactions on Information Theory},
  month = jul,
  volume = {70},
  pages = {5408-5409},
  doi = {10.1109/TIT.2024.3357200},
  author = {Braun, Gábor and Guzmán, Cristóbal and Pokutta, Sebastian},
  title = {Corrections to “Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization Via Information Theory”}
}

Pokutta, S. (2024). The Frank-Wolfe Algorithm: a Short Introduction. Jahresbericht Der Deutschen Mathematiker-Vereinigung, 126(1), 3–35. DOI: 10.1365/s13291-023-00275-x [URL] [arXiv]

[BibTeX]

@article{2023_Pokutta_Frankwolfealgorithm,
  year = {2024},
  journal = {Jahresbericht der Deutschen Mathematiker-Vereinigung},
  month = mar,
  volume = {126},
  number = {1},
  pages = {3–35},
  doi = {10.1365/s13291-023-00275-x},
  url = {https://link.springer.com/article/10.1365/s13291-023-00275-x/fulltext.html},
  archiveprefix = {arXiv},
  eprint = {2311.05313},
  primaryclass = {math.OC},
  author = {Pokutta, Sebastian},
  title = {The Frank-Wolfe Algorithm: a Short Introduction}
}

Deza, A., Pokutta, S., and Pournin, L. (2024). The Complexity of Geometric Scaling. Operations Research Letters, 52. DOI: 10.1016/j.orl.2023.11.010 [arXiv]

[BibTeX]

@article{2022_DezaPokuttaPournin_Geometricscaling,
  year = {2024},
  journal = {Operations Research Letters},
  volume = {52},
  doi = {10.1016/j.orl.2023.11.010},
  archiveprefix = {arXiv},
  eprint = {2205.04063},
  primaryclass = {math.OC},
  author = {Deza, Antoine and Pokutta, Sebastian and Pournin, Lionel},
  title = {The Complexity of Geometric Scaling}
}

Parczyk, O., Pokutta, S., Spiegel, C., and Szabó, T. (2024). New Ramsey Multiplicity Bounds and Search Heuristics. Foundations of Computational Mathematics. DOI: 10.1007/s10208-024-09675-6 [arXiv] [code]

[BibTeX]

@article{2022_ParczykPokuttaSpiegelSzabo_Ramseymultiplicityheuristics,
  year = {2024},
  journal = {Foundations of Computational Mathematics},
  doi = {10.1007/s10208-024-09675-6},
  archiveprefix = {arXiv},
  eprint = {2206.04036},
  primaryclass = {math.CO},
  author = {Parczyk, Olaf and Pokutta, Sebastian and Spiegel, Christoph and Szabó, Tibor},
  title = {New Ramsey Multiplicity Bounds and Search Heuristics},
  code = {https://zenodo.org/record/6602512#.YyvFhi8Rr5g}
}

Deza, A., Onn, S., Pokutta, S., and Pournin, L. (2024). Kissing Polytopes. SIAM Journal on Discrete Mathematics. [arXiv]

[BibTeX]

@article{2023_DezaShmuelPokuttaPournin_Kissingpolytopes,
  year = {2024},
  journal = {SIAM Journal on Discrete Mathematics},
  archiveprefix = {arXiv},
  eprint = {2305.18597},
  primaryclass = {math.MG},
  author = {Deza, Antoine and Onn, Shmuel and Pokutta, Sebastian and Pournin, Lionel},
  title = {Kissing Polytopes}
}

Stengl, S.-M., Gelß, P., Klus, S., and Pokutta, S. (2024). Existence and Uniqueness of Solutions of the Koopman–von Neumann Equation on Bounded Domains. Journal of Physics A: Mathematical and Theoretical. DOI: 10.1088/1751-8121/ad6f7d [URL] [arXiv]

[BibTeX]

@article{2023_StenglGelssKlusPokutta_Koopmanvonneumann,
  year = {2024},
  journal = {Journal of Physics A: Mathematical and Theoretical},
  doi = {10.1088/1751-8121/ad6f7d},
  url = {https://iopscience.iop.org/article/10.1088/1751-8121/ad6f7d},
  archiveprefix = {arXiv},
  eprint = {2306.13504},
  primaryclass = {math.AP},
  author = {Stengl, Steven-Marian and Gelß, Patrick and Klus, Stefan and Pokutta, Sebastian},
  title = {Existence and Uniqueness of Solutions of the Koopman--von Neumann Equation on Bounded Domains}
}

Designolle, S., Vértesi, T., and Pokutta, S. (2024). Symmetric Multipartite Bell Inequalities Via Frank-Wolfe Algorithms. Physics Review A. [arXiv]

[BibTeX]

@article{2024_DesignolleVertesiPokutta_SymmetricBellinequalities,
  year = {2024},
  journal = {Physics Review A},
  archiveprefix = {arXiv},
  eprint = {2310.20677},
  primaryclass = {quant-ph},
  author = {Designolle, Sébastien and Vértesi, Tamás and Pokutta, Sebastian},
  title = {Symmetric Multipartite Bell Inequalities Via Frank-Wolfe Algorithms}
}

Mundinger, K., Pokutta, S., Spiegel, C., and Zimmer, M. (2024). Extending the Continuum of Six-Colorings. Geombinatorics Quarterly, XXXIV. [URL] [arXiv]

[BibTeX]

@article{2024_MundingerPokuttaSpiegelZimmer_SixcoloringsExpansion,
  year = {2024},
  journal = {Geombinatorics Quarterly},
  volume = {XXXIV},
  url = {https://geombina.uccs.edu/past-issues/volume-xxxiv},
  archiveprefix = {arXiv},
  eprint = {2404.05509},
  primaryclass = {math.CO},
  author = {Mundinger, Konrad and Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
  title = {Extending the Continuum of Six-Colorings}
}

Vu‐Han, T. L., Sunkara, V., Bermudez‐Schettino, R., Schwechten, J., Runge, R., Perka, C., Winkler, T., Pokutta, S., Weiß, C., and Pumberger, M. (2024). Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy. Journal of Cachexia, Sarcopenia and Muscle. DOI: 10.1002/jcsm.13599 [URL]

[BibTeX]

@article{2024_Pokutta_PredictionScoliosis,
  year = {2024},
  journal = {Journal of Cachexia, Sarcopenia and Muscle},
  doi = {10.1002/jcsm.13599},
  url = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcsm.13599},
  author = {Vu‐Han, Tu‐Lan and Sunkara, Vikram and Bermudez‐Schettino, Rodrigo and Schwechten, Jakob and Runge, Robin and Perka, Carsten and Winkler, Tobias and Pokutta, Sebastian and Weiß, Claudia and Pumberger, Matthias},
  title = {Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy}
}

Designolle, S., Iommazzo, G., Besançon, M., Knebel, S., Gelß, P., and Pokutta, S. (2023). Improved Local Models and New Bell Inequalities Via Frank-Wolfe Algorithms. Physical Review Research, 5(4). DOI: 10.1103/PhysRevResearch.5.043059 [arXiv] [slides] [code]

[BibTeX]

@article{2023_DesignolleEtAl_LocalmodelsBellinequalities,
  year = {2023},
  journal = {Physical Review Research},
  month = oct,
  volume = {5},
  number = {4},
  doi = {10.1103/PhysRevResearch.5.043059},
  archiveprefix = {arXiv},
  eprint = {2302.04721},
  primaryclass = {quant-ph},
  author = {Designolle, Sébastien and Iommazzo, Gabriele and Besançon, Mathieu and Knebel, Sebastian and Gelß, Patrick and Pokutta, Sebastian},
  title = {Improved Local Models and New Bell Inequalities Via Frank-Wolfe Algorithms},
  code = {https://github.com/ZIB-IOL/BellPolytopes.jl},
  slides = {https://www.pokutta.com/slides/20230808-tokyo-bell.pdf}
}

Kevin-Martin, A., Bärmann, A., Braun, K., Liers, F., Pokutta, S., Schneider, O., Sharma, K., and Tschuppik, S. (2023). Data-driven Distributionally Robust Optimization Over Time. INFORMS Journal on Optimization, 5(4), 376–394. DOI: 10.1287/ijoo.2023.0091 [URL] [arXiv]

[BibTeX]

@article{2023_KevinEtAl_Datadrivendistributionallyrobust,
  year = {2023},
  journal = {INFORMS Journal on Optimization},
  month = oct,
  volume = {5},
  number = {4},
  pages = {376-394},
  doi = {10.1287/ijoo.2023.0091},
  url = {https://pubsonline.informs.org/doi/pdf/10.1287/ijoo.2023.0091},
  archiveprefix = {arXiv},
  eprint = {2304.05377},
  primaryclass = {math.OC},
  author = {Kevin-Martin, Aigner and Bärmann, Andreas and Braun, Kristin and Liers, Frauke and Pokutta, Sebastian and Schneider, Oskar and Sharma, Kartikey and Tschuppik, Sebastian},
  title = {Data-driven Distributionally Robust Optimization Over Time}
}

Bienstock, D., Muñoz, G., and Pokutta, S. (2023). Principled Deep Neural Network Training Through Linear Programming. Discrete Optimization, 49. DOI: 10.1016/j.disopt.2023.100795 [arXiv] [summary]

[BibTeX]

@article{2018_DanielGonzaloPokutta_Polyhedraltraining,
  year = {2023},
  journal = {Discrete Optimization},
  month = aug,
  volume = {49},
  doi = {10.1016/j.disopt.2023.100795},
  archiveprefix = {arXiv},
  eprint = {1810.03218},
  primaryclass = {cs.LG},
  author = {Bienstock, Daniel and Muñoz, Gonzalo and Pokutta, Sebastian},
  title = {Principled Deep Neural Network Training Through Linear Programming},
  summary = {https://www.pokutta.com/blog/research/2018/10/12/DNN-learning-lp-abstract.html}
}

Hunkenschröder, C., Pokutta, S., and Weismantel, R. (2023). Minimizing a Low-dimensional Convex Function Over a High-dimensional Cube. SIAM Journal on Optimization, 33(2), 538–552. DOI: 10.1137/22M1489988 [arXiv]

[BibTeX]

@article{2022_HunkenschrderPokuttaWeismantel_Convexoptimization,
  year = {2023},
  journal = {SIAM Journal on Optimization},
  month = jun,
  volume = {33},
  number = {2},
  pages = {538-552},
  doi = {10.1137/22M1489988},
  archiveprefix = {arXiv},
  eprint = {2204.05266},
  primaryclass = {math.OC},
  author = {Hunkenschröder, Christoph and Pokutta, Sebastian and Weismantel, Robert},
  title = {Minimizing a Low-dimensional Convex Function Over a High-dimensional Cube}
}

Combettes, C., and Pokutta, S. (2023). Revisiting the Approximate Carathéodory Problem Via the Frank-Wolfe Algorithm. Mathematical Programming A, 197, 191–214. DOI: 10.1007/s10107-021-01735-x [URL] [arXiv] [slides] [code] [video]

[BibTeX]

@article{2023_CombettesPokutta_RevisitingApproximateCaratheodory,
  year = {2023},
  journal = {Mathematical Programming A},
  volume = {197},
  pages = {191-214},
  doi = {10.1007/s10107-021-01735-x},
  url = {https://rdcu.be/cCnPL},
  archiveprefix = {arXiv},
  eprint = {1911.04415},
  primaryclass = {math.OC},
  author = {Combettes, Cyrille and Pokutta, Sebastian},
  title = {Revisiting the Approximate Carathéodory Problem Via the Frank-Wolfe Algorithm},
  code = {https://colab.research.google.com/drive/1GLGRTc2jFYy9CqqoVnZgIFVQgAC0c3aZ},
  slides = {https://app.box.com/s/f0zuvr45qa6etidd06i1wart58o7bc8t},
  video = {https://youtube.com/watch?v=VB1e0HrDmVo}
}

Kreimeier, T., Pokutta, S., Walther, A., and Woodstock, Z. (2023). On a Frank-Wolfe Approach for Abs-smooth Functions. Optimization Methods and Software. [arXiv]

[BibTeX]

@article{2023_KreimeierPokuttaWaltherWoodstock_Frankwolfeabssmooth,
  year = {2023},
  journal = {Optimization Methods and Software},
  archiveprefix = {arXiv},
  eprint = {2303.09881},
  primaryclass = {math.OC},
  author = {Kreimeier, Timo and Pokutta, Sebastian and Walther, Andrea and Woodstock, Zev},
  title = {On a Frank-Wolfe Approach for Abs-smooth Functions}
}

Besançon, M., Carderera, A., and Pokutta, S. (2022). FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank-Wolfe Algorithms and Conditional Gradients. INFORMS Journal on Computing. [arXiv] [summary] [slides] [code]

[BibTeX]

@article{2021_BesanconCardereraPokutta_Frankwolfetoolbox,
  year = {2022},
  journal = {INFORMS Journal on Computing},
  month = feb,
  archiveprefix = {arXiv},
  eprint = {2104.06675},
  primaryclass = {math.OC},
  author = {Besançon, Mathieu and Carderera, Alejandro and Pokutta, Sebastian},
  title = {FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank-Wolfe Algorithms and Conditional Gradients},
  code = {https://github.com/ZIB-IOL/FrankWolfe.jl},
  slides = {https://pokutta.com/slides/20210710_FW-simpleSteps-SelfConcordance.pdf},
  summary = {https://pokutta.com/blog/research/2021/04/20/FrankWolfejl.html}
}

Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2022). Restarting Frank-Wolfe. Journal of Optimization Theory and Applications, 192, 799–829. DOI: 10.1007/s10957-021-01989-7 [URL] [arXiv] [slides]

[BibTeX]

@article{2019_KerdrexDaspremontPokutta_RestartingFrankWolfe,
  year = {2022},
  journal = {Journal of Optimization Theory and Applications},
  volume = {192},
  pages = {799-829},
  doi = {10.1007/s10957-021-01989-7},
  url = {https://dx.doi.org/10.1007/s10957-021-01989-7},
  archiveprefix = {arXiv},
  eprint = {1810.02429},
  primaryclass = {math.OC},
  author = {Kerdreux, Thomas and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Restarting Frank-Wolfe},
  slides = {https://app.box.com/s/prd32r6xmuef2k4gah23rd0egllz9rv5}
}

Sofranac, B., Gleixner, A., and Pokutta, S. (2022). Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices. Parallel Computing, 109, 102874. DOI: 10.1016/j.parco.2021.102874 [arXiv] [summary]

[BibTeX]

@article{2020_SofranacGleixnerPokutta_Domainpropagation,
  year = {2022},
  journal = {Parallel Computing},
  volume = {109},
  pages = {102874},
  doi = {10.1016/j.parco.2021.102874},
  archiveprefix = {arXiv},
  eprint = {2009.07785},
  primaryclass = {cs.DC},
  author = {Sofranac, Boro and Gleixner, Ambros and Pokutta, Sebastian},
  title = {Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices},
  summary = {https://pokutta.com/blog/research/2020/09/20/gpu-prob.html}
}

Sofranac, B., Gleixner, A., and Pokutta, S. (2022). An Algorithm-independent Measure of Progress for Linear Constraint Propagation. Constraints, 27, 432–455. DOI: 10.1007/s10601-022-09338-9 [arXiv]

[BibTeX]

@article{2021_SofranacGleixnerPokutta_Progressmeasure,
  year = {2022},
  journal = {Constraints},
  volume = {27},
  pages = {432-455},
  doi = {10.1007/s10601-022-09338-9},
  archiveprefix = {arXiv},
  eprint = {2106.07573},
  primaryclass = {math.OC},
  author = {Sofranac, Boro and Gleixner, Ambros and Pokutta, Sebastian},
  title = {An Algorithm-independent Measure of Progress for Linear Constraint Propagation}
}

Faenza, Y., Muñoz, G., and Pokutta, S. (2022). New Limits of Treewidth-based Tractability in Optimization. Mathematical Programming A, 191, 559–594. [URL] [arXiv]

[BibTeX]

@article{2022_FaenzaMunozPokutta_NewLimitsTreewidth,
  year = {2022},
  journal = {Mathematical Programming A},
  volume = {191},
  pages = {559-594},
  url = {https://link.springer.com/article/10.1007/s10107-020-01563-5},
  archiveprefix = {arXiv},
  eprint = {1807.02551},
  primaryclass = {cs.DM},
  author = {Faenza, Yuri and Muñoz, Gonzalo and Pokutta, Sebastian},
  title = {New Limits of Treewidth-based Tractability in Optimization}
}

Kossen, T., Hirzel, M. A., Madai, V. I., Boenisch, F., Hennemuth, A., Hildebrand, K., Pokutta, S., Sharma, K., Hilbert, A., Sobesky, J., Galinovic, I., Khalil, A. A., Fiebach, J. B., and Frey, D. (2022). Towards Sharing Brain Images: Differentially Private TOF-MRA Images with Segmentation Labels Using Generative Adversarial Networks. Frontiers in Artificial Intelligence. DOI: 10.3389/frai.2022.813842

[BibTeX]

@article{2022_KossenEtAl_Brainimagesharing,
  year = {2022},
  journal = {Frontiers in Artificial Intelligence},
  doi = {10.3389/frai.2022.813842},
  author = {Kossen, Tabea and Hirzel, Manuel A. and Madai, Vince I. and Boenisch, Franziska and Hennemuth, Anja and Hildebrand, Kristian and Pokutta, Sebastian and Sharma, Kartikey and Hilbert, Adam and Sobesky, Jan and Galinovic, Ivana and Khalil, Ahmed A. and Fiebach, Jochen B. and Frey, Dietmar},
  title = {Towards Sharing Brain Images: Differentially Private TOF-MRA Images with Segmentation Labels Using Generative Adversarial Networks}
}

Combettes, C., and Pokutta, S. (2021). Complexity of Linear Minimization and Projection on Some Sets. Operations Research Letters, 49(4). [arXiv] [code]

[BibTeX]

@article{2021_CombettesPokutta_ComplexityLinearMinimization,
  year = {2021},
  journal = {Operations Research Letters},
  month = jul,
  volume = {49},
  number = {4},
  archiveprefix = {arXiv},
  eprint = {2101.10040},
  primaryclass = {math.OC},
  author = {Combettes, Cyrille and Pokutta, Sebastian},
  title = {Complexity of Linear Minimization and Projection on Some Sets},
  code = {https://github.com/cyrillewcombettes/complexity}
}

Kerdreux, T., Roux, C., d’Aspremont, A., and Pokutta, S. (2021). Linear Bandits on Uniformly Convex Sets. Journal of Machine Learning Research, 22(284), 1–23. [URL] [arXiv] [summary]

[BibTeX]

@article{2021_KerdreuxRouxDaspremontPokutta_Linearbandits,
  year = {2021},
  journal = {Journal of Machine Learning Research},
  month = mar,
  volume = {22},
  number = {284},
  pages = {1–23},
  url = {http://jmlr.org/papers/v22/21-0277.html},
  archiveprefix = {arXiv},
  eprint = {2103.05907},
  primaryclass = {cs.LG},
  author = {Kerdreux, Thomas and Roux, Christophe and d'Aspremont, Alexandre and Pokutta, Sebastian},
  title = {Linear Bandits on Uniformly Convex Sets},
  summary = {https://www.pokutta.com/blog/research/2021/04/03/linearBandits.html}
}

Pokutta, S. (2021). Mathematik, Machine Learning Und Artificial Intelligence. Mitteilungen Der DMV. [URL]

[BibTeX]

@article{2021_Pokutta_MathematikMachineLearning,
  year = {2021},
  journal = {Mitteilungen der DMV},
  month = jan,
  url = {https://app.box.com/s/8u6fsucm78e1shyyzoghxar40f7xk6ni},
  author = {Pokutta, Sebastian},
  title = {Mathematik, Machine Learning Und Artificial Intelligence}
}

Anari, N., Haghtalab, N., Naor, S., Pokutta, S., Singh, M., and Torrico Palacios, A. (2021). Structured Robust Submodular Maximization: Offline and Online Algorithms. INFORMS Journal on Computing, 33(4), 1259–1684. [URL] [arXiv]

[BibTeX]

@article{2019_AnariHaghtalabNaorPokuttaSinghTorrico_StructuredRobustSubmodular,
  year = {2021},
  journal = {INFORMS Journal on Computing},
  volume = {33},
  number = {4},
  pages = {1259-1684},
  url = {https://pubsonline.informs.org/doi/abs/10.1287/ijoc.2020.0998},
  archiveprefix = {arXiv},
  eprint = {1710.04740},
  primaryclass = {cs.DS},
  author = {Anari, N. and Haghtalab, N. and Naor, S. and Pokutta, Sebastian and Singh, Mohit and Torrico Palacios, Alfredo},
  title = {Structured Robust Submodular Maximization: Offline and Online Algorithms}
}

Braun, G., Pokutta, S., and Zink, D. (2019). Affine Reductions for LPs and SDPs. Mathematical Programming, 173, 281–312. DOI: 10.1007/s10107-017-1221-9 [arXiv]

[BibTeX]

@article{2014_BraunPokuttaZink_Affinereductions,
  year = {2019},
  journal = {Mathematical Programming},
  volume = {173},
  pages = {281–312},
  doi = {10.1007/s10107-017-1221-9},
  archiveprefix = {arXiv},
  eprint = {1410.8816},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Pokutta, Sebastian and Zink, Daniel},
  title = {Affine Reductions for LPs and SDPs}
}

Bazzi, A., Fiorini, S., Pokutta, S., and Svensson, O. (2019). Small Linear Programs Cannot Approximate Vertex Cover Within a Factor of 2 - Ε. Mathematics of Operations Research, 44(1), 1–375. [arXiv] [slides]

[BibTeX]

@article{2015_BazziFioriniPokuttaSvensson_SmallLinearPrograms,
  year = {2019},
  journal = {Mathematics of Operations Research},
  volume = {44},
  number = {1},
  pages = {1-375},
  archiveprefix = {arXiv},
  eprint = {1503.00753},
  primaryclass = {cs.CC},
  author = {Bazzi, A. and Fiorini, S. and Pokutta, Sebastian and Svensson, O.},
  title = {Small Linear Programs Cannot Approximate Vertex Cover Within a Factor of 2 - Ε},
  slides = {https://app.box.com/s/00aqupo722bbpmdcyzwt8xmfqzyu14iy}
}

Braun, G., Pokutta, S., and Zink, D. (2019). Lazifying Conditional Gradient Algorithms. The Journal of Machine Learning Research, 20(71), 1–42. [URL] [arXiv]

[BibTeX]

@article{2016_BraunPokuttaZink_Lazifyinggradientalgorithms,
  year = {2019},
  journal = {The Journal of Machine Learning Research},
  volume = {20},
  number = {71},
  pages = {1–42},
  url = {https://jmlr.org/papers/v20/18-114.html},
  archiveprefix = {arXiv},
  eprint = {1610.05120},
  primaryclass = {cs.DS},
  author = {Braun, Gábor and Pokutta, Sebastian and Zink, Daniel},
  title = {Lazifying Conditional Gradient Algorithms}
}

Braun, G., Pokutta, S., and Roy, A. (2018). Strong Reductions for Extended Formulations. Mathematical Programming, 172, 591–620. DOI: 10.1007/s10107-018-1316-y [arXiv]

[BibTeX]

@article{2015_BraunPokuttaRoy_Strongreductions,
  year = {2018},
  journal = {Mathematical Programming},
  month = nov,
  volume = {172},
  pages = {591–620},
  doi = {10.1007/s10107-018-1316-y},
  archiveprefix = {arXiv},
  eprint = {1512.04932},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Pokutta, Sebastian and Roy, Aurko},
  title = {Strong Reductions for Extended Formulations}
}

Le Bodic, P., Pfetsch, M., Pavelka, J., and Pokutta, S. (2018). Solving MIPs Via Scaling-based Augmentation. Discrete Optimization, 27, 1–25. DOI: 10.1016/j.disopt.2017.08.004 [arXiv]

[BibTeX]

@article{2018_LebodicPfetschPavelkaPokutta_SolvingMIPs,
  year = {2018},
  journal = {Discrete Optimization},
  volume = {27},
  pages = {1-25},
  doi = {10.1016/j.disopt.2017.08.004},
  archiveprefix = {arXiv},
  eprint = {1509.03206},
  primaryclass = {math.OC},
  author = {Le Bodic, P. and Pfetsch, Marc and Pavelka, Jeff and Pokutta, Sebastian},
  title = {Solving MIPs Via Scaling-based Augmentation}
}

Song, R., Xie, Y., and Pokutta, S. (2018). On the Effect of Model Mismatch for Sequential Info-Greedy Sensing. EURASIP Journal on Advances in Signal Processing. [URL]

[BibTeX]

@article{2018_SongXiePokutta_EffectModelMismatch,
  year = {2018},
  journal = {EURASIP Journal on Advances in Signal Processing},
  url = {https://asp-eurasipjournals.springeropen.com/articles/10.1186/s13634-018-0551-y},
  author = {Song, R. and Xie, Yao and Pokutta, Sebastian},
  title = {On the Effect of Model Mismatch for Sequential Info-Greedy Sensing}
}

Braun, G., Brown-Cohen, J., Huq, A., Pokutta, S., Raghavendra, P., Roy, A., Weitz, B., and Zink, D. (2017). The Matching Problem Has No Small Symmetric SDP. Mathematical Programming, 165, 643–662. DOI: 10.1007/s10107-016-1098-z [arXiv]

[BibTeX]

@article{2015_BraunEtAl_MatchingproblemSdp,
  year = {2017},
  journal = {Mathematical Programming},
  month = oct,
  volume = {165},
  pages = {643–662},
  doi = {10.1007/s10107-016-1098-z},
  archiveprefix = {arXiv},
  eprint = {1504.00703},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Brown-Cohen, Jonah and Huq, Arefin and Pokutta, Sebastian and Raghavendra, Prasad and Roy, Aurko and Weitz, Benjamin and Zink, Daniel},
  title = {The Matching Problem Has No Small Symmetric SDP}
}

Braun, G., Guzmán, C., and Pokutta, S. (2017). Unifying Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization. IEEE Transactions on Information Theory, 63(7), 4709–4724. DOI: 10.1109/TIT.2017.2701343 [arXiv]

[BibTeX]

@article{2014_BraunGuzmanPokutta_Lowerboundsoraclecomplexity,
  year = {2017},
  journal = {IEEE Transactions on Information Theory},
  month = jul,
  volume = {63},
  number = {7},
  pages = {4709-4724},
  doi = {10.1109/TIT.2017.2701343},
  archiveprefix = {arXiv},
  eprint = {1407.5144},
  primaryclass = {math.OC},
  author = {Braun, Gábor and Guzmán, Cristóbal and Pokutta, Sebastian},
  title = {Unifying Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization}
}

Bodur, M., Del Pia, A., Dey, S. S., Molinaro, M., and Pokutta, S. (2017). Aggregation-based Cutting-planes for Packing and Covering Integer Programs. Mathematical Programming A. DOI: 10.1007/s10107-017-1192-x [arXiv]

[BibTeX]

@article{2017_BodurDelpiaDeyMolinaroPokutta_AggregationBasedCutting,
  year = {2017},
  journal = {Mathematical Programming A},
  doi = {10.1007/s10107-017-1192-x},
  archiveprefix = {arXiv},
  eprint = {1606.08951},
  primaryclass = {math.OC},
  author = {Bodur, Merve and Del Pia, Alberto and Dey, Santanu Sabush and Molinaro, Marco and Pokutta, Sebastian},
  title = {Aggregation-based Cutting-planes for Packing and Covering Integer Programs}
}

Braun, G., Jain, R., Lee, T., and Pokutta, S. (2017). Information-theoretic Approximations of the Nonnegative Rank. Computational Complexity, 26, 147–197. DOI: 10.1007/s00037-016-0125-z [URL]

[BibTeX]

@article{2017_BraunRahulTroyPokutta_Informationtheoreticnonnegativerank,
  year = {2017},
  journal = {Computational Complexity},
  volume = {26},
  pages = {147–197},
  doi = {10.1007/s00037-016-0125-z},
  url = {https://eccc.weizmann.ac.il/report/2013/158},
  author = {Braun, Gábor and Jain, Rahul and Lee, Troy and Pokutta, Sebastian},
  title = {Information-theoretic Approximations of the Nonnegative Rank}
}

Christensen, H., Khan, A., Pokutta, S., and Tetali, P. (2017). Multidimensional Bin Packing and Other Related Problems: A Survey. Computer Science Review. [URL]

[BibTeX]

@article{2017_ChristensenKhanPokuttaTetali_MultidimensionalBinPacking,
  year = {2017},
  journal = {Computer Science Review},
  url = {https://sciencedirect.com/science/article/pii/S1574013716301356},
  author = {Christensen, H. and Khan, A. and Pokutta, Sebastian and Tetali, P.},
  title = {Multidimensional Bin Packing and Other Related Problems: A Survey}
}

Knueven, B., Ostrowski, J., and Pokutta, S. (2017). Detecting Almost Symmetries in Graphs. Mathematical Programming C. [URL]

[BibTeX]

@article{2017_KnuevenOstrowskiPokutta_DetectingAlmostSymmetries,
  year = {2017},
  journal = {Mathematical Programming C},
  url = {https://link.springer.com/article/10.1007/s12532-017-0124-3},
  author = {Knueven, B. and Ostrowski, J. and Pokutta, Sebastian},
  title = {Detecting Almost Symmetries in Graphs}
}

Martin, A., Müller, J., Pape, S., Peter, A., Pokutta, S., and Winter, T. (2017). Pricing and Clearing Combinatorial Markets with Singleton and Swap Orders. Mathematical Methods of Operations Research, 85(2), 155–177. [arXiv]

[BibTeX]

@article{2017_MartinMullerPapePeterPokuttaWinter_PricingClearing,
  year = {2017},
  journal = {Mathematical Methods of Operations Research},
  volume = {85},
  number = {2},
  pages = {155-177},
  archiveprefix = {arXiv},
  eprint = {1404.6546},
  primaryclass = {math.OC},
  author = {Martin, Alexander and Müller, Johannes and Pape, S. and Peter, A. and Pokutta, Sebastian and Winter, T.},
  title = {Pricing and Clearing Combinatorial Markets with Singleton and Swap Orders}
}

Roy, A., and Pokutta, S. (2017). Hierarchical Clustering Via Spreading Metrics. Journal of Machine Learning Research, 18, 1–35. [URL] [arXiv]

[BibTeX]

@article{2017_RoyPokutta_HierarchicalClustering,
  year = {2017},
  journal = {Journal of Machine Learning Research},
  volume = {18},
  pages = {1-35},
  url = {https://jmlr.org/papers/v18/17-081.html},
  archiveprefix = {arXiv},
  eprint = {1610.09269},
  primaryclass = {cs.LG},
  author = {Roy, Aurko and Pokutta, Sebastian},
  title = {Hierarchical Clustering Via Spreading Metrics}
}

Braun, G., Firorini, S., and Pokutta, S. (2016). Average Case Polyhedral Complexity of the Maximum Stable Set Problem. Mathematical Programming, 160(1), 407–431. DOI: 10.1007/s10107-016-0989-3 [arXiv]

[BibTeX]

@article{2013_BraunSamuelPokutta_Averagepolyhedralcomplexity,
  year = {2016},
  journal = {Mathematical Programming},
  month = mar,
  volume = {160},
  number = {1},
  pages = {407–431},
  doi = {10.1007/s10107-016-0989-3},
  archiveprefix = {arXiv},
  eprint = {1311.4001},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Firorini, Samuel and Pokutta, Sebastian},
  title = {Average Case Polyhedral Complexity of the Maximum Stable Set Problem}
}

Braun, G., and Pokutta, S. (2016). Common Information and Unique Disjointness. Algorithmica, 76(3), 597–629. DOI: 10.1007/s00453-016-0132-0 [URL]

[BibTeX]

@article{2016_BraunPokutta_CommoninformationDisjointness,
  year = {2016},
  journal = {Algorithmica},
  month = feb,
  volume = {76},
  number = {3},
  pages = {597–629},
  doi = {10.1007/s00453-016-0132-0},
  url = {https://eccc.weizmann.ac.il/report/2013/056},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {Common Information and Unique Disjointness}
}

Braun, G., and Pokutta, S. (2016). A Polyhedral Characterization of Border Bases. SIAM Journal on Discrete Mathematics, 30(1), 239–265. DOI: 10.1137/140977990 [arXiv]

[BibTeX]

@article{2009_BraunPokutta_BorderbasesOrderidealsPolyhedral,
  year = {2016},
  journal = {SIAM Journal on Discrete Mathematics},
  volume = {30},
  number = {1},
  pages = {239–265},
  doi = {10.1137/140977990},
  archiveprefix = {arXiv},
  eprint = {0912.1502},
  primaryclass = {math.AC},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {A Polyhedral Characterization of Border Bases}
}

Bärmann, A., Heidt, A., Martin, A., Pokutta, S., and Thurner, C. (2016). Polyhedral Approximation of Ellipsoidal Uncertainty Sets Via Extended Formulations - a Computational Case Study. Computational Management Science, 13(2), 151–193. DOI: 10.1007/s10287-015-0243-0 [URL]

[BibTeX]

@article{2016_BarmannHeidtMartinPokuttaThurner_PolyhedralApproximation,
  year = {2016},
  journal = {Computational Management Science},
  volume = {13},
  number = {2},
  pages = {151-193},
  doi = {10.1007/s10287-015-0243-0},
  url = {https://link.springer.com/article/10.1007/s10287-015-0243-0},
  author = {Bärmann, Andreas and Heidt, Andreas and Martin, Alexander and Pokutta, Sebastian and Thurner, Christoph},
  title = {Polyhedral Approximation of Ellipsoidal Uncertainty Sets Via Extended Formulations - a Computational Case Study}
}

Gatzert, N., Pokutta, S., and Vogl, N. (2016). Convergence of Capital and Insurance Markets: Pricing Aspects of Index-Linked Catastrophic Loss Instruments. Journal of Risk and Insurance. [URL]

[BibTeX]

@article{2016_GatzertPokuttaVogl_ConvergenceCapitalInsurance,
  year = {2016},
  journal = {Journal of Risk and Insurance},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2320370},
  author = {Gatzert, Nadine and Pokutta, Sebastian and Vogl, Nikolai},
  title = {Convergence of Capital and Insurance Markets: Pricing Aspects of Index-Linked Catastrophic Loss Instruments}
}

Braun, G., Firorini, S., Pokutta, S., and Steurer, D. (2015). Approximation Limits of Linear Programs (beyond Hierarchies). Mathematics of Operations Research, 40(3), 756–772. DOI: 10.1287/moor.2014.0694 [arXiv]

[BibTeX]

@article{2012_BraunSamuelPokuttaSteurer_Approximationlimits,
  year = {2015},
  journal = {Mathematics of Operations Research},
  month = aug,
  volume = {40},
  number = {3},
  pages = {756-772},
  doi = {10.1287/moor.2014.0694},
  archiveprefix = {arXiv},
  eprint = {1204.0957},
  primaryclass = {cs.CC},
  author = {Braun, Gábor and Firorini, Samuel and Pokutta, Sebastian and Steurer, David},
  title = {Approximation Limits of Linear Programs (beyond Hierarchies)}
}

Braun, G., Pokutta, S., and Xie, Y. (2015). Info-greedy Sequential Adaptive Compressed Sensing. IEEE Journal of Selected Topics in Signal Processing, 9(4), 601–611. DOI: 10.1109/JSTSP.2015.2400428 [arXiv]

[BibTeX]

@article{2014_BraunPokuttaYao_Infogreedycompressedsensing,
  year = {2015},
  journal = {IEEE Journal of Selected Topics in Signal Processing},
  month = jun,
  volume = {9},
  number = {4},
  pages = {601–611},
  doi = {10.1109/JSTSP.2015.2400428},
  archiveprefix = {arXiv},
  eprint = {1407.0731},
  primaryclass = {cs.IT},
  author = {Braun, Gábor and Pokutta, Sebastian and Xie, Yao},
  title = {Info-greedy Sequential Adaptive Compressed Sensing}
}

Fiorini, S., Massar, S., Pokutta, S., Tiwary, H. R., and de Wolf, R. (2015). Exponential Lower Bounds for Polytopes in Combinatorial Optimization. Journal of the ACM, 62(2), 1–17. DOI: 10.1145/2716307 [arXiv]

[BibTeX]

@article{2012_FioriniMassarPokuttaTiwaryWolf_LinearVsSemidefinite,
  year = {2015},
  journal = {Journal of the ACM},
  volume = {62},
  number = {2},
  pages = {1-17},
  doi = {10.1145/2716307},
  archiveprefix = {arXiv},
  eprint = {1111.0837},
  primaryclass = {math.CO},
  author = {Fiorini, S. and Massar, S. and Pokutta, Sebastian and Tiwary, H.R. and de Wolf, R.},
  title = {Exponential Lower Bounds for Polytopes in Combinatorial Optimization}
}

Briet, J., Dadush, D., and Pokutta, S. (2015). On the Existence of 0/1 Polytopes with High Semidefinite Extension Complexity. Mathematical Programming B, 153(1), 179–199. [arXiv]

[BibTeX]

@article{2013_BrietDadushPokutta_ExistencePolytopes,
  year = {2015},
  journal = {Mathematical Programming B},
  volume = {153},
  number = {1},
  pages = {179-199},
  archiveprefix = {arXiv},
  eprint = {1305.3268},
  primaryclass = {cs.CC},
  author = {Briet, Jop and Dadush, Daniel and Pokutta, Sebastian},
  title = {On the Existence of 0/1 Polytopes with High Semidefinite Extension Complexity}
}

Lee, D., and Pokutta, S. (2015). Toward a Science of Autonomy for Physical Systems: Transportation. Computing Community Consortium White Paper. [URL] [arXiv]

[BibTeX]

@article{2015_LeePokutta_TowardScienceAutonomy,
  year = {2015},
  journal = {Computing Community Consortium White Paper},
  url = {https://cra.org/ccc/files/docs/white-papers/AutonomousSystems/Transportation%20v3.pdf},
  archiveprefix = {arXiv},
  eprint = {1609.05821},
  primaryclass = {cs.CY},
  author = {Lee, D. and Pokutta, Sebastian},
  title = {Toward a Science of Autonomy for Physical Systems: Transportation}
}

Braun, G., and Pokutta, S. (2014). A Short Proof for the Polyhedrality of the Chvátal-Gomory Closure of a Compact Convex Set. Operations Research Letters, 42(5), 307–310. DOI: 10.1016/j.orl.2014.05.004 [arXiv]

[BibTeX]

@article{2012_BraunPokutta_Chvtalgomoryclosure,
  year = {2014},
  journal = {Operations Research Letters},
  month = jul,
  volume = {42},
  number = {5},
  pages = {307–310},
  doi = {10.1016/j.orl.2014.05.004},
  archiveprefix = {arXiv},
  eprint = {1207.4884},
  primaryclass = {math.CO},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {A Short Proof for the Polyhedrality of the Chvátal-Gomory Closure of a Compact Convex Set}
}

Dey, S. S., and Pokutta, S. (2014). Design and Verify: a New Scheme for Generating Cutting-planes. Mathematical Programming A, 145, 199–222. DOI: 10.1007/978-3-642-20807-2_12 [URL]

[BibTeX]

@article{2011_DeyPokutta_DesignVerify,
  year = {2014},
  journal = {Mathematical Programming A},
  volume = {145},
  pages = {199-222},
  doi = {10.1007/978-3-642-20807-2_12},
  url = {https://optimization-online.org/2011/04/3002},
  author = {Dey, Santanu Sabush and Pokutta, Sebastian},
  title = {Design and Verify: a New Scheme for Generating Cutting-planes}
}

Schmaltz, C., Pokutta, S., Heidorn, T., and Andrae, S. (2014). How to Make Regulators and Shareholders Happy Under Basel III. Journal of Banking and Finance, 311–325. DOI: 10.1016/j.jbankfin.2014.05.031 [URL]

[BibTeX]

@article{2013_SchmaltzPokuttaHeidornAndrae_BaselIII,
  year = {2014},
  journal = {Journal of Banking and Finance},
  pages = {311-325},
  doi = {10.1016/j.jbankfin.2014.05.031},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2179490},
  author = {Schmaltz, Christian and Pokutta, Sebastian and Heidorn, Thomas and Andrae, Silvio},
  title = {How to Make Regulators and Shareholders Happy Under Basel III}
}

Drewes, S., and Pokutta, S. (2014). Computing Discrete Expected Utility Maximizing Portfolios. Journal of Investing, 23(4), 121–132. [URL]

[BibTeX]

@article{2014_DrewesPokutta_ComputingDiscreteExpected,
  year = {2014},
  journal = {Journal of Investing},
  volume = {23},
  number = {4},
  pages = {121-132},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1662729},
  author = {Drewes, Sarah and Pokutta, Sebastian},
  title = {Computing Discrete Expected Utility Maximizing Portfolios}
}

Drewes, S., and Pokutta, S. (2014). Symmetry-exploiting Cuts for a Class of Mixed-0/1 Second Order Cone Programs. Discrete Optimization, 13, 23–35. DOI: 10.1016/j.disopt.2014.04.002 [URL]

[BibTeX]

@article{2014_DrewesPokutta_SymmetryExploitingCuts,
  year = {2014},
  journal = {Discrete Optimization},
  volume = {13},
  pages = {23-35},
  doi = {10.1016/j.disopt.2014.04.002},
  url = {https://optimization-online.org/2010/06/2652},
  author = {Drewes, Sarah and Pokutta, Sebastian},
  title = {Symmetry-exploiting Cuts for a Class of Mixed-0/1 Second Order Cone Programs}
}

Martin, A., Müller, J., and Pokutta, S. (2014). Strict Linear Prices in Non-convex European Day-ahead Electricity Markets. Optimization Methods and Software, 29(1), 189–221. DOI: 10.1080/10556788.2013.823544 [URL] [arXiv]

[BibTeX]

@article{2014_MartinMullerPokutta_StrictLinearPrices,
  year = {2014},
  journal = {Optimization Methods and Software},
  volume = {29},
  number = {1},
  pages = {189-221},
  doi = {10.1080/10556788.2013.823544},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1660528},
  archiveprefix = {arXiv},
  eprint = {1203.4177},
  primaryclass = {math.OC},
  author = {Martin, Alexander and Müller, Johannes and Pokutta, Sebastian},
  title = {Strict Linear Prices in Non-convex European Day-ahead Electricity Markets}
}

Kroll, C., and Pokutta, S. (2013). Just a Perfect Day: Developing a Happiness Optimised Day Schedule. Journal of Economic Psychology, 34, 210–217. DOI: 10.1016/j.joep.2012.09.015 [URL] [video]

[BibTeX]

@article{2013_KrollPokutta_PerfectDay,
  year = {2013},
  journal = {Journal of Economic Psychology},
  volume = {34},
  pages = {210-217},
  doi = {10.1016/j.joep.2012.09.015},
  url = {https://sciencedirect.com/science/article/pii/S0167487012001158},
  author = {Kroll, C. and Pokutta, Sebastian},
  title = {Just a Perfect Day: Developing a Happiness Optimised Day Schedule},
  video = {https://youtube.com/watch?v=IOMtP0ygL74}
}

Pokutta, S., and Van Vyve, M. (2013). A Note on the Extension Complexity of the Knapsack Polytope. Operations Research Letters, 41, 347–350. DOI: 10.1016/j.orl.2013.03.010 [URL]

[BibTeX]

@article{2013_PokuttaVanvyve_NoteExtension,
  year = {2013},
  journal = {Operations Research Letters},
  volume = {41},
  pages = {347-350},
  doi = {10.1016/j.orl.2013.03.010},
  url = {https://optimization-online.org/2013/02/3787},
  author = {Pokutta, Sebastian and Van Vyve, M.},
  title = {A Note on the Extension Complexity of the Knapsack Polytope}
}

Braun, G., and Pokutta, S. (2012). Rigid Abelian Groups and the Probabilistic Method. Contemporary Mathematcs, 576, 17–30. DOI: 10.1090/conm/576 [arXiv]

[BibTeX]

@article{2011_BraunPokutta_Rigidabeliangroups,
  year = {2012},
  journal = {Contemporary Mathematcs},
  volume = {576},
  pages = {17–30},
  doi = {10.1090/conm/576},
  archiveprefix = {arXiv},
  eprint = {1107.2325},
  primaryclass = {math.GR},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {Rigid Abelian Groups and the Probabilistic Method}
}

Göbel, R., and Pokutta, S. (2012). Absolutely Rigid Fields and Shelah’s Absolutely Rigid Trees. Contemporary Mathematics, 576, 105–128. DOI: 10.1090/conm/576

[BibTeX]

@article{2012_GobelPokutta_AbsolutelyRigidFields,
  year = {2012},
  journal = {Contemporary Mathematics},
  volume = {576},
  pages = {105-128},
  doi = {10.1090/conm/576},
  author = {Göbel, R. and Pokutta, Sebastian},
  title = {Absolutely Rigid Fields and Shelah's Absolutely Rigid Trees}
}

Pokutta, S., and Schmaltz, C. (2012). Optimal Planning Under Basel III Regulations. Cass-Capco Institute Paper Series on Risk, 34. [URL]

[BibTeX]

@article{2012_PokuttaSchmaltz_OptimalPlanning,
  year = {2012},
  journal = {Cass-Capco Institute Paper Series on Risk},
  volume = {34},
  url = {https://capco.com/capco-institute/capco-journal/journal-34-cass-capco-institute-paper-series-on-risk},
  author = {Pokutta, Sebastian and Schmaltz, Christian},
  title = {Optimal Planning Under Basel III Regulations}
}

Braun, G., and Pokutta, S. (2011). Random Half-integral Polytopes. Operations Research Letters, 39(3), 204–207. DOI: 10.1016/j.orl.2011.03.003 [URL]

[BibTeX]

@article{2011_BraunPokutta_Randomhalfintegralpolytopes,
  year = {2011},
  journal = {Operations Research Letters},
  month = may,
  volume = {39},
  number = {3},
  pages = {204–207},
  doi = {10.1016/j.orl.2011.03.003},
  url = {https://optimization-online.org/2010/11/2813},
  author = {Braun, Gábor and Pokutta, Sebastian},
  title = {Random Half-integral Polytopes}
}

Haus, U. U., Hemmecke, R., and Pokutta, S. (2011). Reconstructing Biochemical Cluster Networks. Journal of Mathematical Chemistry, 49(10), 2441–2456. DOI: 10.1007/s10910-011-9892-6 [arXiv]

[BibTeX]

@article{2011_HausHemmeckePokutta_ReconstructingBiochemical,
  year = {2011},
  journal = {Journal of Mathematical Chemistry},
  volume = {49},
  number = {10},
  pages = {2441-2456},
  doi = {10.1007/s10910-011-9892-6},
  archiveprefix = {arXiv},
  eprint = {0906.1342},
  primaryclass = {math.AC},
  author = {Haus, U.U. and Hemmecke, R. and Pokutta, Sebastian},
  title = {Reconstructing Biochemical Cluster Networks}
}

Letchford, A. N., Pokutta, S., and Schulz, A. S. (2011). On the Membership Problem for the 0,1/2-closure. Operations Research Letters, 39(5), 301–304. DOI: 10.1016/j.orl.2011.07.003

[BibTeX]

@article{2011_LetchfordPokuttaSchulz_MembershipProblem,
  year = {2011},
  journal = {Operations Research Letters},
  volume = {39},
  number = {5},
  pages = {301-304},
  doi = {10.1016/j.orl.2011.07.003},
  author = {Letchford, A.N. and Pokutta, Sebastian and Schulz, Andreas S.},
  title = {On the Membership Problem for the {0,1/2}-closure}
}

Pokutta, S., and Schmaltz, C. (2011). Managing Liquidity: Optimal Degree of Centralization. Journal of Banking and Finance, 35, 627–638. DOI: 10.1016/j.jbankfin.2010.07.001 [URL]

[BibTeX]

@article{2011_PokuttaSchmaltz_ManagingLiquidity,
  year = {2011},
  journal = {Journal of Banking and Finance},
  volume = {35},
  pages = {627-638},
  doi = {10.1016/j.jbankfin.2010.07.001},
  url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1458963},
  author = {Pokutta, Sebastian and Schmaltz, Christian},
  title = {Managing Liquidity: Optimal Degree of Centralization}
}

Pokutta, S., and Schulz, A. S. (2011). Integer-empty Polytopes in the 0/1-cube with Maximal Gomory-Chvátal Rank. Operations Research Letters, 39(6), 457–460. DOI: 10.1016/j.orl.2011.09.004 [URL]

[BibTeX]

@article{2011_PokuttaSchulz_IntegerEmptyPolytopes,
  year = {2011},
  journal = {Operations Research Letters},
  volume = {39},
  number = {6},
  pages = {457-460},
  doi = {10.1016/j.orl.2011.09.004},
  url = {https://optimization-online.org/2010/12/2850},
  author = {Pokutta, Sebastian and Schulz, Andreas S.},
  title = {Integer-empty Polytopes in the 0/1-cube with Maximal Gomory-Chvátal Rank}
}

Pokutta, S., and Stauffer, G. (2011). Lower Bounds for the Chvátal-Gomory Rank in the 0/1 Cube. Operations Research Letters, 39(3), 200–203. DOI: 10.1016/j.orl.2011.03.001 [URL]

[BibTeX]

@article{2011_PokuttaStauffer_LowerBoundChvatal,
  year = {2011},
  journal = {Operations Research Letters},
  volume = {39},
  number = {3},
  pages = {200-203},
  doi = {10.1016/j.orl.2011.03.001},
  url = {https://optimization-online.org/2010/09/2748},
  author = {Pokutta, Sebastian and Stauffer, G.},
  title = {Lower Bounds for the Chvátal-Gomory Rank in the 0/1 Cube}
}

Drewes, S., and Pokutta, S. (2010). Cutting-planes for Weakly-coupled 0/1 Second Order Cone Programs. Electronic Notes in Discrete Mathematics, 36, 735–742. DOI: 10.1016/j.endm.2010.05.093

[BibTeX]

@article{2010_DrewesPokutta_CuttingPlanes,
  year = {2010},
  journal = {Electronic Notes in Discrete Mathematics},
  volume = {36},
  pages = {735-742},
  doi = {10.1016/j.endm.2010.05.093},
  author = {Drewes, Sarah and Pokutta, Sebastian},
  title = {Cutting-planes for Weakly-coupled 0/1 Second Order Cone Programs}
}

Heldt, D., Kreuzer, M., Pokutta, S., and Poulisse, H. (2009). Approximate Computation of Zero-dimensional Polynomial Ideals. Journal of Symbolic Computation, 44, 1566–1591. DOI: 10.1016/j.jsc.2008.11.010

[BibTeX]

@article{2009_HeldtKreuzerPokuttaPoulisse_ApproximateComputation,
  year = {2009},
  journal = {Journal of Symbolic Computation},
  volume = {44},
  pages = {1566-1591},
  doi = {10.1016/j.jsc.2008.11.010},
  author = {Heldt, D. and Kreuzer, M. and Pokutta, Sebastian and Poulisse, H.},
  title = {Approximate Computation of Zero-dimensional Polynomial Ideals}
}

Pokutta, S., and Stauffer, G. (2009). France Telecom Workforce Scheduling Problem: a Challenge. RAIRO-Operations Research, 43, 375–386. DOI: 10.1051/ro/2009025

[BibTeX]

@article{2009_PokuttaStauffer_FranceTelecom,
  year = {2009},
  journal = {RAIRO-Operations Research},
  number = {43},
  pages = {375-386},
  doi = {10.1051/ro/2009025},
  author = {Pokutta, Sebastian and Stauffer, G.},
  title = {France Telecom Workforce Scheduling Problem: a Challenge}
}

Droste, M., Göbel, R., and Pokutta, S. (2008). Absolute Graphs with Prescribed Endomorphism Monoid. Semigroup Forum, 76(2), 256–267. DOI: 10.1007/s00233-007-9029-1 [URL]

[BibTeX]

@article{2008_DrosteGobelPokutta_AbsoluteGraphs,
  year = {2008},
  journal = {Semigroup Forum},
  month = mar,
  volume = {76},
  number = {2},
  pages = {256-267},
  doi = {10.1007/s00233-007-9029-1},
  url = {http://link.springer.com/article/10.1007/s00233-007-9029-1/fulltext.html},
  author = {Droste, M. and Göbel, R. and Pokutta, Sebastian},
  title = {Absolute Graphs with Prescribed Endomorphism Monoid}
}

Göbel, R., and Pokutta, S. (2008). Construction of Dual Modules Using Martin’s Axiom. Journal of Algebra, 320, 2388–2404. DOI: 10.1016/j.jalgebra.2008.06.017 [URL]

[BibTeX]

@article{2008_GobelPokutta_ConstructionDualModules,
  year = {2008},
  journal = {Journal of Algebra},
  volume = {320},
  pages = {2388-2404},
  doi = {10.1016/j.jalgebra.2008.06.017},
  url = {https://sciencedirect.com/science/article/pii/S0021869308003153},
  author = {Göbel, R. and Pokutta, Sebastian},
  title = {Construction of Dual Modules Using Martin's Axiom}
}

Pokutta, S., and Strüngmann, L. (2007). The Chase Radical and Reduced Products. Journal of Pure and Applied Algebra, 211, 532–540. DOI: 10.1016/j.jpaa.2007.02.007

[BibTeX]

@article{2007_PokuttaStrungmann_ChaseRadical,
  year = {2007},
  journal = {Journal of Pure and Applied Algebra},
  volume = {211},
  pages = {532-540},
  doi = {10.1016/j.jpaa.2007.02.007},
  author = {Pokutta, Sebastian and Strüngmann, Lutz},
  title = {The Chase Radical and Reduced Products}
}

Heldt, D., Kreuzer, M., Pokutta, S., and Poulisse, H. (2006). Algebraische Modellierung Mit Methoden Der Approximativen Computer Algebra Und Anwendungen in Der Ölindustrie. OR News, 15–18.

[BibTeX]

@article{2006_HeldtKreuzerPokuttaPoulisse_AlgebraischeModellierung,
  year = {2006},
  journal = {OR News},
  pages = {15-18},
  author = {Heldt, D. and Kreuzer, M. and Pokutta, Sebastian and Poulisse, H.},
  title = {Algebraische Modellierung Mit Methoden Der Approximativen Computer Algebra Und Anwendungen in Der Ölindustrie}
}

Pokutta, S., and Törner, G. (2005). Fixpunktminimierung Bei Binnenschiffen. OR News, 23, 13–17.

[BibTeX]

@article{2005_PokuttaTorner_Fixpunktminimierung,
  year = {2005},
  journal = {OR News},
  volume = {23},
  pages = {13-17},
  author = {Pokutta, Sebastian and Törner, G.},
  title = {Fixpunktminimierung Bei Binnenschiffen}
}

🔬 Projects

AI-Based High-Resolution Forest Monitoring

Preserving global vegetation is crucial for addressing and mitigating climate change. Accurate, up-to-date forest health data is essential. AI4Forest aims to develop advanced AI methods to monitor forests using satellite imagery, including radar and optical data. The project will create scalable techniques for detailed, high-resolution maps of the globe, e.g., to monitor canopy height, biomass, and to track forest disturbances.

AI4Forest

Jun 2023 to May 2027

Decomposition Methods for Mixed-integer Optimal Control

In this project, we study domain decomposition approaches for optimal control in gas transport networks. Our goal is to couple space-time-domain decomposition with machine learning and mixed-integer programming. We will develop NeTI (Network Tearing and Interconnection), a data-driven and physics-informed algorithm combining mixed-integer nonlinear programming, surrogate model learning, and graph decomposition strategies.

TRR-154 A05

Jan 2022 to Jun 2026

Expanding Merlin-Arthur Classifiers: Interpretable Neural Networks Through Interactive Proof Systems

Existing approaches for interpreting Neural Network classifiers that highlight features relevant for a decision are based solely on heuristics. We introduce a theory that allows us to bound the quality of the features without assumptions on the classifier model by relating classification to Interactive Proof Systems.

MATH+ EF1-24

Apr 2023 to Mar 2026

On a Frank-Wolfe Approach for Abs-smooth Optimization

Motivated by nonsmooth problems in machine learning, we solve the problem of minimizing an abs-smooth function subject to closed convex constraints. New theory and algorithms are developed using linear minimization oracles to enforce constraints and abs-linearization methods to handle nonsmoothness.

MATH+ EF1-23

Apr 2023 to Mar 2026

Convex Solver Adaptivity for Mixed-integer Optimization

We will investigate mixed-integer optimization with convex objectives using error-adaptive convex solvers in branch-and-bound. Focusing on improving lower bounds and balancing computational costs, we aim to develop a faster branch-and-bound methodology by leveraging modern MILP techniques and error-adaptive methods. Key aspects include warm-starting and controlled inexactness in early termination.

MATH+ AA3-15

Apr 2023 to Mar 2026

Entanglement Detection Via Frank-Wolfe Algorithms

We will apply a Frank-Wolfe-based approach for separability certification and entanglement detection of multipartite quantum states. The method will be further exploited to derive entanglement witnesses in the case, often encountered in experiments, of incomplete characterisation of the quantum state.

MATH+ AA2-19

Jan 2024 to Dec 2025

LEAN on Me: Transforming Mathematics Through Formal Verification, Improved Tactics, and Machine Learning

Formal proof verification can both ensure proof correctness and provide new tools and insights to mathematicians. The goals of this project include creating resources for students and researchers, verifying relevant results, improving proof tactics, and exploring Machine Learning approaches.

MATH+ AA5-9

Jan 2024 to Dec 2025

Scaling Up Flag Algebras in Combinatorics

This project aims to obtain new bounds in Extremal Combinatorics through an application of flag algebras. The goal is to both improve the underlying computational aspects for existing problems as well as to further develop the theory of flag algebras to extend it to new areas of application.

MATH+ EF1-21

Oct 2022 to Sep 2025

Quantum Algorithms for Optimization

Computational devices and quantum mechanics revolutionized the 20th century. Quantum computation merges these fields to solve optimization problems faster than classical computers. This project aims to develop new quantum algorithms for general-purpose and specific applications, including optimization, mixed-integer programs, and uses in machine learning, logistics, big data, and physics. We will explore quantum dynamic programming, graph sparsification, and QAOA-type algorithms for small quantum computers.

QOPT

May 2022 to Apr 2025

Approximating Combinatorial Optimization Problems

This project will explore to what extent near-term quantum computing may potentially provide better approximations to combinatorial optimization problems, bringing together expertise from quantum computing and applied mathematics. It is a collaborative effort within the Einstein Research Unit on Quantum Devices, involving the Freie Universität Berlin (FU Berlin), the Weierstrass Institute for Applied Analysis and Stochastics (WIAS), and the Zuse Institute Berlin (ZIB).

ACOP

Jan 2022 to Dec 2024

Scaling Methods for Integer Programming

SCALE

Sep 2024 to Oct 2024

Learning Extremal Structures in Combinatorics

Extremal Combinatorics focuses on the maximum or minimum sizes of discrete structures with specific properties, posing significant challenges due to their complexity. Traditional computational approaches often fail due to exponential growth in search spaces, but recent AI advancements, especially in Reinforcement Learning, offer new potential. Applying these AI methods could provide insights into combinatorial problems while also enhancing the understanding of AI techniques in complex, sparse reward environments.

MATH+ EF1-12

Jan 2021 to May 2024

Decision-making for Energy Network Dynamics

We develop theory and algorithms for 0-1 decision making in optimization problems constrained by partial differential equations. By exploring extended formulations, we achieve new stationarity concepts through sequential exact and approximative relaxation of adjoint-based primal-dual optimality conditions.

MATH+ AA4-7

Jun 2021 to May 2024

JSPS Invitational Visiting Professor

JSPS

Dec 2023 to May 2024

MiniMIP: a Faster, More Reliable, and Easier Way to Maintain and Solve MIP Problems

MiniMIP is an open source, machine learning oriented Mixed-Integer Programming (MIP) solver. We provide a range of interfaces for all aspects of solving MIPs (e.g. heuristics, cut generators, LP solvers), supplying users with a constant view of the internal state and allowing them to propose modifications that are integrated into the global state internally.

miniMIP

Jan 2021 to Dec 2023

Sparsity and Sample-size Efficiency in Structured Learning

In this project, we study algorithms that promote sparsity. We develop PageRank optimization algorithms that scale with solution sparsity and investigate Riemannian optimization using manifold geometry. Additionally, we develop algorithms for efficient fair resource allocation based on established fairness axioms.

MATH+ AA5-1

Jan 2022 to Dec 2023

Learning to Schedule Heuristics in IP

Heuristics play a crucial role in exact solvers for Mixed Integer Programming (MIP). However, the question of how to manage multiple MIP heuristics in a solver has not received sufficient attention. This project addresses the strategic management of primal heuristics in MIP solvers, aiming to replace static, hard-coded rules with dynamic, self-improving procedures.

HLEARN

Nov 2021 to Oct 2023

Theoretical Foundations of Deep Learning

Deep learning is revolutionizing real-world applications and science, replacing or complementing classical model-based methods in solving mathematical problems. Despite successes, deep neural networks lack strong theoretical-mathematical foundations. This program aims to develop a comprehensive theoretical foundation of deep learning from three perspectives: statistical, application, and mathematical-methodological. The research is interdisciplinary, combining mathematics, statistics, and theoretical computer science to address complex questions.

SPP 2298, project number 441826958

May 2020 to May 2023

Adaptive Algorithms Through Machine Learning: Exploiting Interactions in Integer Programming

The performance of modern mixed-integer program solvers is highly dependent on a number of interdependent individual components. Using tools from machine learning, we intend to develop an integrated framework that is able to capture interactions of individual decisions made in these components with the ultimate goal to improve performance.

MATH+ EF1-9

Jan 2021 to Dec 2022

Beyond the Worst-case: Data-dependent Rates in Learning and Optimization

Worst-case complexity bounds are increasingly insufficient to explain the (often superior) real-world performance of optimization and learning algorithms. We consider data-dependent rates, approximation guarantees, and complexity bounds to provide guarantees much more in line with actual performance.

MATH+ AA3-7

Jan 2021 to Dec 2022

Daten- Und Prozessbasierte Zustandsermittlung Für Eine Wertorientierte Komponentenbewirtschaftung in Imperfekter Umgebung

Airplane data quality is uneven due to varied sources and sensor limitations. This project aims to create data processing services for Component Spotting to help airlines optimize business processes and improve customer satisfaction. We will develop methods for modeling and evaluating data quality, creating a semantic and uniform description for processing models. Using AI algorithms, we will handle inaccuracies and uncertainties to form an analysis-friendly information model.

DaProko

Jul 2020 to Dec 2022

Globally Optimal Neural Network Training

Training artificial neural networks is a key optimization task in deep learning. To improve generalization, robustness, and explainability, we aim to compute globally optimal solutions. We will use integer programming methods, exploiting mixed-integer nonlinear programming and enhancing solving techniques like spatial branch-and-cut. Additionally, we'll leverage symmetry to reduce computational burden and ensure symmetry in solutions, and incorporate true sparsity using a mixed-integer nonlinear programming framework.

GONNT

Mar 2021 to Feb 2022

Quantum Computing and Integer Programming

Quantum computing has the potential to occupy an important position in the field of computing in the long term. In the short to medium term, however, we can expect the emergence of so-called "Noisy Intermediate-Scale Quantum algorithms" and "Quantum Approximate Optimization Algorithms" in an initial phase. These algorithms can often solve a special subclass of problems approximately and very quickly using quantum computing and are significantly easier to implement technically. In this pilot project, a workflow will be tested, ranging from the design of hybrid quantum-classical algorithms to their simulation using quantum simulators on HPC hardware.

QCIP

Apr 2021 to Dec 2021

💬 Talks and posters

Conference and workshop talks

: Extending the Continuum of Six-Colorings
6th DOxML Conference, Tokyo [PDF]
Dec 2024: Exploring Mixed-Integer Convex Optimization with Conditional Gradients: Foundations and Applications
MIP International Workshop [PDF]
Dec 2024: AI X Algorithms X Applications
NUS School of Computing Seminar
Nov 2024: Extending the Continuum of Six-Colorings
MFO Program: Combinatorial Optimization [PDF]
Jul 2024: German <-> Japanese Supercomputing - a Success Story
16th JHPCN symposium [PDF]
Jun 2024: Cargo-Kult Trifft Auf Große Sprachmodelle: Entmystifizierung von KI?
Lange Nacht der Wissenschaften
Mar 2024: The Cargo Cult Meets Large Language Models: Demystifying AI Sentiments?
Hong Kong Analytics Community Meeting
Mar 2024: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
CUHK-Shenzhen Seminar [PDF]
Mar 2024: Conditional Gradients in Machine Learning
International Workshop on Image Processing and Machine Learning [PDF]
Feb 2024: Conditional Gradients in Machine Learning
NUS Math Seminar [PDF]
Jan 2024: The New AI World Order
Conti AI Vision
Nov 2023: Conditional Gradients in Machine Learning
Workshop on Geometry and Machine Learning, Leipzig [PDF]
Sep 2023: The Approximate Carathéodory Problem and an Application to Quantum Mechanics
7th Workshop on Future Algorithms and Applications, Berlin
Aug 2023: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
ICIAM 2023 Minisymposium: Advances in Optimization I, Tokyo [PDF]
Aug 2023: Improved Local Models and New Bell Inequalities Via Frank-Wolfe Algorithms
5th DOxML Conference, Tokyo [PDF]
Jul 2023: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
Jon-Shmuel Halfway to Twelfty [PDF]
Jun 2023: Möglichkeiten Und Grenzen Künstlicher Intelligenz
Lange Nacht der Wissenschaften, Berlin
Mar 2023: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
ICERM Workshop: Combinatorics and Optimization, Providence [PDF]
Mar 2023: Conditional Gradients -- an Overview
2nd Vienna Workshop on Computational Optimization, Vienna [PDF]
Mar 2023: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
Workshop on Optimization and Machine Learning, Waischenfeld [PDF]
Dec 2022: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
Fields Workshop on Recent Advances in Optimization, Toronto [PDF]
Sep 2022: Convex Integer Optimization with Frank-Wolfe Methods
Advances in Classical and Quantum Algorithms for Optimization and Machine Learning, Tokyo [PDF]
Jul 2022: Structured ML Training Via Conditional Gradients
Workshop on Algorithmic Optimization and Data Science, Trier [PDF]
Nov 2021: Discrete Optimization in Machine Learning - an (informal) Overview
Oberwolfach Workshop on Combinatorial Optimization, Oberwolfach [PDF]
Oct 2021: Fast Algorithms for 1-fair Packing (and Its Dual)
HIM Workshop: Continuous approaches to discrete optimization, Bonn [PDF]
Apr 2021: Learning From Little Data
Google University Visit @ TU Berlin [PDF]
Feb 2021: Structured ML Training Via Conditional Gradients
IPAM Deep Learning and Combinatorial Optimization Workshop [PDF]
Nov 2020: AI And-for-with-against Humanity?
Human-centric Artificial Intelligence: 2nd French-German-Japanese Symposium [PDF]
Sep 2020: Restarting Algorithms: Sometimes There Is Free Lunch
17th CPAIOR Conference [PDF]
Sep 2020: Robust ML Training with Conditional Gradients
4th Computational Optimization at Work (CO@Work), Berlin [PDF]
May 2020: Beyond Worst-case Rates: Data-dependent Rates in Learning and Optimization
17th Mixed Integer Programming European Workshop (MIP) [PDF]
Mar 2020: Künstliche Intelligence Im Arbeitsalltag
Künstliche Intelligenz: verständlich @ TH Wildau, Wildau [PDF]
Sep 2019: Smooth Constraint Convex Minimization Via Conditional Gradients
19th French-German-Swiss conference on Optimization, Nice [PDF]
Sep 2019: Mirror Descent and Related Methods in Linear and Discrete Optimization
Cargese Workshop on Combinatorial Optimization, Cargese [PDF]
Jan 2019: Smooth Constraint Convex Minimization Via Conditional Gradients
INFORMS Optimization Society Conference (IOS), Knoxville [PDF]
Nov 2018: When the AI God Fails: Recent Adventures in AI Hacking, Security, and Fairness
Hong Kong Analytics Community Meeting, Hong Kong [PDF]
Nov 2018: Blended Conditional Gradients
Oberwolfach Workshop on Combinatorial Optimization, Oberwolfach [PDF]
Apr 2018: Emulating the Expert: Inverse Optimization Through Online Learning
Optimization and Discrete Geometry Workshop, Tel Aviv [PDF]

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Research seminar talks

May 2023: Alternating Linear Minimization: Revisiting von Neumann's Alternating Projections
University of Magdeburg MathCoRe Lecture, Magdeburg [PDF]
Apr 2023: Conditional Gradients in Machine Learning
Yale Statistics and Data Science Seminar Series, New Haven [PDF]
Mar 2023: Structured ML Training Via Conditional Gradients
Columbia IEOR Seminar Series, New York [PDF]
Apr 2022: Conditional Gradients in Machine Learning and Optimization
IST ELLIS Seminar Series, Klosterneuburg [PDF]
Sep 2021: Conditional Gradients - a Tour D'horizon
AI Campus Berlin Tech Lunch Talk [PDF]
May 2021: Conditional Gradients in Machine Learning and Optimization
Math+ Friday Colloquium
Nov 2020: Conditional Gradients: Overview and Recent Advances
RWTH Aachen Mathematical Colloquium [PDF]
Jul 2019: Locally Accelerated Conditional Gradients
Research Institute for Mathematical Sciences Seminar, Kyoto University, Kyoto [PDF]

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🌍 Research Stays and Visits

Feb 2024: National University of Singapore hosted by Rahul Jain
Feb 2024: Tsinghua University hosted by Tsinghua
Mar 2024: City University of Hong Kong in Shenzhen hosted by Zhi-Quan Luo
Mar 2024: Hong Kong Analytics Society hosted by Hong Kong Analytics Society
Apr 2024: University of Tokyo hosted by Akiko Takeda
Nov 2024: National University of Singapore hosted by Sanjay Jain

📅 Event Attendance

May 2025: 7th DOxML Conference, Kyoto
Jul 2025: 8th International Conference on Continuous Optimization (ICCOPT), Los Angeles
Sep 2023: 5th Computational Optimization at Work (CO@Work), Berlin