Sebastian Pokutta

department head at ZIB since September 2019
professor at TUB since September 2019
vice president at ZIB since September 2019

📬 Contact

office Room 3026 at ZIB
Room MA 606 at TUB
e-mail pokutta (at) zib.de
pokutta (at) math.tu-berlin.de
homepage pokutta.com

🎓 Academic Background

2005 Ph.D. in Mathematics at DUE
2003 Diploma in Mathematics at DUE

🔬 Research

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.

Preprints

  1. Mundinger, K., Zimmer, M., and Pokutta, S. (2024). Neural Parameter Regression for Explicit Representations of PDE Solution Operators. [arXiv]
    [BibTeX]
    @misc{NeuralRegressionPDE2024,
      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}
    }
  2. Roux, C., Zimmer, M., and Pokutta, S. (2024). On the Byzantine-resilience of Distillation-based Federated Learning. [arXiv]
    [BibTeX]
    @misc{byzantinefederated2024,
      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}
    }
  3. Göß, A., Martin, A., Pokutta, S., and Sharma, K. (2024). Norm-induced Cuts: Optimization with Lipschitzian Black-box Functions. [URL] [arXiv]
    [BibTeX]
    @misc{gmps_nic_23,
      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}
    }
  4. 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{FWopenLoopAccelerate2023,
      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}
    }
  5. Stengl, S.-M., Gelß, P., Klus, S., and Pokutta, S. (2023). Existence and Uniqueness of Solutions of the Koopman–von Neumann Equation on Bounded Domains. [arXiv]
    [BibTeX]
    @misc{KoopmanNeumann2023,
      archiveprefix = {arXiv},
      eprint = {2306.13504},
      primaryclass = {math.AP},
      year = {2023},
      author = {Stengl, Steven-Marian and GelĂź, Patrick and Klus, Stefan and Pokutta, Sebastian},
      title = {Existence and Uniqueness of Solutions of the Koopman--von Neumann Equation on Bounded Domains}
    }
  6. Sadiku, S., Wagner, M., and Pokutta, S. (2023). Group-wise Sparse and Explainable Adversarial Attacks. [arXiv]
    [BibTeX]
    @misc{groupadversarialattack2023,
      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}
    }
  7. Deza, A., Onn, S., Pokutta, S., and Pournin, L. (2023). Kissing Polytopes. [arXiv]
    [BibTeX]
    @misc{kissing_polytopes_2023,
      archiveprefix = {arXiv},
      eprint = {2305.18597},
      primaryclass = {math.MG},
      year = {2023},
      author = {Deza, Antoine and Onn, Shmuel and Pokutta, Sebastian and Pournin, Lionel},
      title = {Kissing Polytopes}
    }
  8. 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. (2023). Quantum Optimization: Potential, Challenges, and the Path Forward. [arXiv]
    [BibTeX]
    @misc{qopc_path2023,
      archiveprefix = {arXiv},
      eprint = {2312.02279},
      primaryclass = {quant-ph},
      year = {2023},
      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 Tapia, Elena Peña 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 = {Quantum Optimization: Potential, Challenges, and the Path Forward}
    }
  9. Scieur, D., Kerdreux, T., Martínez-Rubio, D., d’Aspremont, A., and Pokutta, S. (2023). Strong Convexity of Sets in Riemannian Manifolds. [arXiv]
    [BibTeX]
    @misc{skmap_strong_convexity_of_sets_in_riemannian_manifolds_23,
      archiveprefix = {arXiv},
      eprint = {2312.03583},
      primaryclass = {math.OC},
      year = {2023},
      author = {Scieur, Damien and Kerdreux, Thomas and MartĂ­nez-Rubio, David and d'Aspremont, Alexandre and Pokutta, Sebastian},
      title = {Strong Convexity of Sets in Riemannian Manifolds}
    }
  10. Woodstock, Z., and Pokutta, S. (2023). Splitting the Conditional Gradient Algorithm. [arXiv]
    [BibTeX]
    @misc{splitcg2023,
      archiveprefix = {arXiv},
      eprint = {2311.05381},
      primaryclass = {math.OC},
      year = {2023},
      author = {Woodstock, Zev and Pokutta, Sebastian},
      title = {Splitting the Conditional Gradient Algorithm}
    }
  11. 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{zasp_perp_23,
      archiveprefix = {arXiv},
      eprint = {2312.15230},
      primaryclass = {cs.LG},
      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}
    }
  12. Braun, G., Pokutta, S., and Weismantel, R. (2022). Alternating Linear Minimization: Revisiting von Neumann’s Alternating Projections. [arXiv] [slides] [video]
    [BibTeX]
    @misc{alternating_lmo_2022,
      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}
    }
  13. Braun, G., Carderera, A., Combettes, C., Hassani, H., Karbasi, A., Mokhtari, A., and Pokutta, S. (2022). Conditional Gradient Methods. [arXiv]
    [BibTeX]
    @misc{fw_survey_2022,
      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}
    }
  14. GelĂź, P., Klus, S., Shakibaei, Z., and Pokutta, S. (2022). Low-rank Tensor Decompositions of Quantum Circuits. [arXiv]
    [BibTeX]
    @misc{gksp_lowrankqc_22,
      archiveprefix = {arXiv},
      eprint = {2205.09882},
      primaryclass = {quant-ph},
      year = {2022},
      author = {GelĂź, Patrick and Klus, Stefan and Shakibaei, Zarin and Pokutta, Sebastian},
      title = {Low-rank Tensor Decompositions of Quantum Circuits}
    }
  15. Hendrych, D., Troppens, H., Besançon, M., and Pokutta, S. (2022). Convex Integer Optimization with Frank-Wolfe Methods. [arXiv] [slides] [code]
    [BibTeX]
    @misc{htbp_cio_22,
      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}
    }
  16. Zimmer, M., Spiegel, C., and Pokutta, S. (2022). Compression-aware Training of Neural Networks Using Frank-Wolfe. [arXiv]
    [BibTeX]
    @misc{zsp_deepsparsefw_22,
      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}
    }
  17. Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2021). Local and Global Uniform Convexity Conditions. Preprint. [arXiv]
    [BibTeX]
    @article{KAP2021,
      arxiv = {https://arxiv.org/abs/2102.05134},
      author = {Kerdreux, Thomas and d'Aspremont, Alexandre and Pokutta, Sebastian},
      month = feb,
      journal = {preprint},
      title = {{Local and Global Uniform Convexity Conditions}},
      year = {2021}
    }
  18. Carderera, A., Pokutta, S., Schütte, C., and Weiser, M. (2021). CINDy: Conditional gradient-based Identification of Non-linear Dynamics – Noise-robust recovery. Preprint. [arXiv] [summary]
    [BibTeX]
    @article{PSZ2020,
      arxiv = {https://arxiv.org/abs/2101.02630},
      author = {Carderera, Alejandro and Pokutta, Sebastian and SchĂĽtte, Christof and Weiser, Martin},
      month = jan,
      journal = {preprint},
      summary = {http://www.pokutta.com/blog/research/2021/01/16/cindy.html},
      title = {{CINDy: Conditional gradient-based Identification of Non-linear Dynamics -- Noise-robust recovery}},
      year = {2021}
    }
  19. Braun, G., and Pokutta, S. (2021). Dual Prices for Frank–Wolfe Algorithms. [arXiv]
    [BibTeX]
    @misc{dual_prices_FW_2021,
      archiveprefix = {arXiv},
      eprint = {2101.02087},
      primaryclass = {math.OC},
      year = {2021},
      author = {Braun, Gábor and Pokutta, Sebastian},
      title = {Dual Prices for Frank–Wolfe Algorithms}
    }
  20. Roux, C., Wirth, E., Pokutta, S., and Kerdreux, T. (2021). Efficient Online-bandit Strategies for Minimax Learning Problems. [arXiv]
    [BibTeX]
    @misc{online.bandit-minimax_2021,
      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}
    }
  21. Combettes, C., Spiegel, C., and Pokutta, S. (2020). Projection-free Adaptive Gradients for Large-scale Optimization. [arXiv] [summary] [code]
    [BibTeX]
    @misc{csp_adafw_20,
      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}
    }
  22. Pokutta, S., Spiegel, C., and Zimmer, M. (2020). Deep Neural Network Training with Frank-Wolfe. [arXiv] [summary] [code]
    [BibTeX]
    @misc{zsp_deepfw_20,
      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}
    }
  23. Carderera, A., and Pokutta, S. (2020). Second-order Conditional Gradient Sliding. Preprint. [arXiv] [summary] [code]
    [BibTeX]
    @article{CaP2020,
      arxiv = {https://arxiv.org/abs/2002.08907},
      author = {Carderera, Alejandro and Pokutta, Sebastian},
      code = {https://github.com/pokutta/Second-order-Conditional-Gradients},
      journal = {{preprint}},
      summary = {http://www.pokutta.com/blog/research/2020/06/20/socgs.html},
      title = {{Second-order Conditional Gradient Sliding}},
      year = {2020}
    }
  24. Bärmann, A., Martin, A., Pokutta, S., and Schneider, O. (2018). An Online-Learning Approach to Inverse Optimization. Submitted. [arXiv] [summary] [slides]
    [BibTeX]
    @article{BPS2017jour,
      arxiv = {https://arxiv.org/abs/1810.12997},
      author = {B{\"a}rmann, Andreas and Martin, Alexander and Pokutta, Sebastian and Schneider, Oskar},
      journal = {Submitted},
      slides = {https://app.box.com/s/7ti8sz8mf5s2znn1qo32in4jxy5gjnn1},
      summary = {http://www.pokutta.com/blog/research/2018/11/25/expertLearning-abstract.html},
      title = {{An Online-Learning Approach to Inverse Optimization}},
      year = {2018}
    }
  25. Braun, G., and Pokutta, S. (2016). An Efficient High-probability Algorithm for Linear Bandits. [arXiv]
    [BibTeX]
    @misc{Braun2016bandit,
      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}
    }
  26. Braun, G., and Pokutta, S. (2015). An Information Diffusion Fano Inequality. [arXiv]
    [BibTeX]
    @misc{Braun2015Fano,
      archiveprefix = {arXiv},
      eprint = {1504.05492},
      primaryclass = {cs.IT},
      year = {2015},
      author = {Braun, Gábor and Pokutta, Sebastian},
      title = {An Information Diffusion Fano Inequality}
    }

Conference proceedings

  1. Sharma, K., Hendrych, D., Besançon, M., and Pokutta, S. (2024). Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe. Proceedings of INFORMS Optimization Society Conference. [arXiv]
    [BibTeX]
    @inproceedings{SharmaNetworkDesignTrafficFrankWolfe24,
      year = {2024},
      booktitle = {Proceedings of 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}
    }
  2. 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 International Conference on Machine Learning.
    [BibTeX]
    @inproceedings{canopy2024,
      year = {2024},
      booktitle = {Proceedings of International Conference on Machine Learning},
      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}
    }
  3. Hendrych, D., Besançon, M., and Pokutta, S. (2024). Solving the Optimal Experiment Design Problem with Mixed-integer Convex Methods. Proceedings of Symposium on Experimental Algorithms. [arXiv]
    [BibTeX]
    @inproceedings{design_of_experiments_boscia_23,
      year = {2024},
      booktitle = {Proceedings of Symposium on Experimental Algorithms},
      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}
    }
  4. Kiem, A., Pokutta, S., and Spiegel, C. (2024). Categorification of Flag Algebras. Proceedings of Discrete Mathematics Days.
    [BibTeX]
    @inproceedings{kps_flagalgebracategory_24,
      year = {2024},
      booktitle = {Proceedings of Discrete Mathematics Days},
      author = {Kiem, Aldo and Pokutta, Sebastian and Spiegel, Christoph},
      title = {Categorification of Flag Algebras}
    }
  5. Kiem, A., Pokutta, S., and Spiegel, C. (2024). The 4-color Ramsey Multiplicity of Triangles. Proceedings of Discrete Mathematics Days. [arXiv] [code]
    [BibTeX]
    @inproceedings{kps_flagalgebrasymmetries_22,
      year = {2024},
      booktitle = {Proceedings of Discrete Mathematics Days},
      archiveprefix = {arXiv},
      eprint = {2312.08049},
      primaryclass = {math.CO},
      author = {Kiem, Aldo and Pokutta, Sebastian and Spiegel, Christoph},
      title = {The 4-color Ramsey Multiplicity of Triangles},
      code = {https://github.com/FordUniver/kps_trianglemult}
    }
  6. Mundinger, K., Pokutta, S., Spiegel, C., and Zimmer, M. (2024). Extending the Continuum of Six-Colorings. Proceedings of Discrete Mathematics Days. [arXiv]
    [BibTeX]
    @inproceedings{mpsz_hadwigernelsonspectrum_24:1,
      year = {2024},
      booktitle = {Proceedings of Discrete Mathematics Days},
      archiveprefix = {arXiv},
      eprint = {2404.05509},
      author = {Mundinger, Konrad and Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
      title = {Extending the Continuum of Six-Colorings}
    }
  7. MartĂ­nez-Rubio, D., Roux, C., and Pokutta, S. (2024). Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point. Proceedings of International Conference on Machine Learning. [arXiv]
    [BibTeX]
    @inproceedings{mrp_tradeoffs_riemannian_gradient_descent_23,
      year = {2024},
      booktitle = {Proceedings of International Conference on Machine Learning},
      archiveprefix = {arXiv},
      eprint = {2403.10429},
      primaryclass = {math.OC},
      author = {MartĂ­nez-Rubio, David and Roux, Christophe and Pokutta, Sebastian},
      title = {Convergence and Trade-offs in Riemannian Gradient Descent and Riemannian Proximal Point}
    }
  8. Wäldchen, S., Sharma, K., Zimmer, M., Turan, B., and Pokutta, S. (2024). Merlin-Arthur Classifiers: Formal Interpretability with Interactive Black Boxes. Proceedings of International Conference on Artificial Intelligence and Statistics. [arXiv]
    [BibTeX]
    @inproceedings{wszp_merlinarthur_22,
      year = {2024},
      booktitle = {Proceedings of International Conference on Artificial Intelligence and Statistics},
      archiveprefix = {arXiv},
      eprint = {2206.00759},
      primaryclass = {cs.LG},
      author = {Wäldchen, Stephan and Sharma, Kartikey and Zimmer, Max and Turan, Berkant and Pokutta, Sebastian},
      title = {Merlin-Arthur Classifiers: Formal Interpretability with Interactive Black Boxes}
    }
  9. Zimmer, M., Spiegel, C., and Pokutta, S. (2024). Sparse Model Soups: A Recipe for Improved Pruning Via Model Averaging. Proceedings of International Conference on Learning Representations. [arXiv]
    [BibTeX]
    @inproceedings{zsp_modelsoup_23,
      year = {2024},
      booktitle = {Proceedings of International Conference on Learning Representations},
      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}
    }
  10. Chmiela, A., Gleixner, A., Lichocki, P., and Pokutta, S. (2023). Online Learning for Scheduling MIP Heuristics. Proceedings of International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 114–123. DOI: 10.1007/978-3-031-33271-5_8
    [BibTeX]
    @inproceedings{ChmielaGleixnerLichockiPokutta2023_OnlineLearning,
      year = {2023},
      booktitle = {Proceedings of 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},
      author = {Chmiela, Antonia and Gleixner, Ambros and Lichocki, Pawel and Pokutta, Sebastian},
      title = {Online Learning for Scheduling MIP Heuristics}
    }
  11. Thuerck, D., Sofranac, B., Pfetsch, M., and Pokutta, S. (2023). Learning Cuts Via Enumeration Oracles. Proceedings of Conference on Neural Information Processing Systems. [arXiv]
    [BibTeX]
    @inproceedings{learn_cut_oracle_2023,
      year = {2023},
      booktitle = {Proceedings of 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}
    }
  12. MartĂ­nez-Rubio, D., and Pokutta, S. (2023). Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. Proceedings of Annual Workshop on Computational Learning Theory. [arXiv]
    [BibTeX]
    @inproceedings{mp_acceleratedriemannian_22:1,
      year = {2023},
      booktitle = {Proceedings of Annual Workshop on Computational Learning Theory},
      archiveprefix = {arXiv},
      eprint = {2211.14645},
      primaryclass = {math.OC},
      author = {MartĂ­nez-Rubio, David and Pokutta, Sebastian},
      title = {Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties}
    }
  13. MartĂ­nez-Rubio, D., Roux, C., Criscitiello, C., and Pokutta, S. (2023). Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2023). [arXiv]
    [BibTeX]
    @inproceedings{mrp_accelerated_minmax_riemannian_23,
      year = {2023},
      booktitle = {Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2023)},
      archiveprefix = {arXiv},
      eprint = {2305.16186},
      primaryclass = {math.OC},
      author = {MartĂ­nez-Rubio, David and Roux, Christophe and Criscitiello, Christopher and Pokutta, Sebastian},
      title = {Accelerated Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties}
    }
  14. MartĂ­nez-Rubio, D., Wirth, E., and Pokutta, S. (2023). Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond. Proceedings of Annual Workshop on Computational Learning Theory. [arXiv]
    [BibTeX]
    @inproceedings{mwp_accelerated_sparse_pagerank_23,
      year = {2023},
      booktitle = {Proceedings of Annual Workshop on Computational Learning Theory},
      archiveprefix = {arXiv},
      eprint = {2303.12875},
      primaryclass = {math.OC},
      author = {MartĂ­nez-Rubio, David and Wirth, Elias and Pokutta, Sebastian},
      title = {Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond}
    }
  15. Parczyk, O., Pokutta, S., Spiegel, C., and SzabĂł, T. (2023). Fully Computer-assisted Proofs in Extremal Combinatorics. Proceedings of AAAI Conference on Artificial Intelligence. [arXiv] [slides] [code]
    [BibTeX]
    @inproceedings{ppss_ramsey_22,
      year = {2023},
      booktitle = {Proceedings of AAAI Conference on Artificial Intelligence},
      archiveprefix = {arXiv},
      eprint = {2206.04036},
      primaryclass = {math.CO},
      author = {Parczyk, Olaf and Pokutta, Sebastian and Spiegel, Christoph and SzabĂł, Tibor},
      title = {Fully Computer-assisted Proofs in Extremal Combinatorics},
      code = {https://zenodo.org/record/6602512#.YyvFhi8Rr5g},
      slides = {https://pokutta.com/slides/20220705_DMD22_RamseyMultiplicity.pdf}
    }
  16. Wirth, E., Kerdreux, T., and Pokutta, S. (2023). Acceleration of Frank-Wolfe Algorithms with Open Loop Step-sizes. Proceedings of International Conference on Artificial Intelligence and Statistics. [arXiv]
    [BibTeX]
    @inproceedings{wkp_openloop_22,
      year = {2023},
      booktitle = {Proceedings of 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}
    }
  17. Wirth, E., Kera, H., and Pokutta, S. (2023). Approximate Vanishing Ideal Computations at Scale. Proceedings of International Conference on Learning Representations. [arXiv] [slides]
    [BibTeX]
    @inproceedings{wkp_vanishingideal_22,
      year = {2023},
      booktitle = {Proceedings of 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}
    }
  18. Zimmer, M., Spiegel, C., and Pokutta, S. (2023). How I Learned to Stop Worrying and Love Retraining. Proceedings of International Conference on Learning Representations. [arXiv] [code]
    [BibTeX]
    @inproceedings{zsp_retrain_21,
      year = {2023},
      booktitle = {Proceedings of International Conference on Learning Representations},
      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}
    }
  19. 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 Conference on Neural Information Processing Systems, 176, 220–231. [URL] [arXiv]
    [BibTeX]
    @inproceedings{GasseEtal2022_ML4CO,
      year = {2022},
      booktitle = {Proceedings of 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}
    }
  20. Criado, F., MartĂ­nez-Rubio, D., and Pokutta, S. (2022). Fast Algorithms for Packing Proportional Fairness and Its Dual. Proceedings of Conference on Neural Information Processing Systems. [arXiv] [poster]
    [BibTeX]
    @inproceedings{cmp_packing_proportional_fairness_22,
      year = {2022},
      booktitle = {Proceedings of Conference on Neural Information Processing Systems},
      archiveprefix = {arXiv},
      eprint = {2109.03678},
      primaryclass = {math.OC},
      author = {Criado, Francisco and MartĂ­nez-Rubio, David and Pokutta, Sebastian},
      title = {Fast Algorithms for Packing Proportional Fairness and Its Dual},
      poster = {https://pokutta.com/slides/20211105_fairpacking-poster.pdf}
    }
  21. Macdonald, J., Besançon, M., and Pokutta, S. (2022). Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings. Proceedings of International Conference on Machine Learning. [arXiv] [poster] [video]
    [BibTeX]
    @inproceedings{mbp_interpretfw_22,
      year = {2022},
      booktitle = {Proceedings of 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}
    }
  22. MartĂ­nez-Rubio, D., and Pokutta, S. (2022). Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2022). [URL] [arXiv] [poster]
    [BibTeX]
    @inproceedings{mp_acceleratedriemannian_22,
      year = {2022},
      booktitle = {Proceedings of Optimization for Machine Learning (NeurIPS Workshop OPT 2022)},
      url = {https://opt-ml.org/papers/2022/paper27.pdf},
      archiveprefix = {arXiv},
      eprint = {2211.14645},
      primaryclass = {math.OC},
      author = {MartĂ­nez-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}
    }
  23. Parczyk, O., Pokutta, S., Spiegel, C., and SzabĂł, T. (2022). New Ramsey Multiplicity Bounds and Search Heuristics. Proceedings of Discrete Mathematics Days. [arXiv] [code]
    [BibTeX]
    @inproceedings{ppss_ramsey_22:1,
      year = {2022},
      booktitle = {Proceedings of Discrete Mathematics Days},
      archiveprefix = {arXiv},
      eprint = {2206.04036},
      primaryclass = {math.CO},
      author = {Parczyk, Olaf and Pokutta, Sebastian and Spiegel, Christoph and SzabĂł, Tibor},
      title = {New Ramsey Multiplicity Bounds and Search Heuristics},
      code = {https://zenodo.org/record/6602512#.YyvFhi8Rr5g}
    }
  24. Tsuji, K., Tanaka, K., and Pokutta, S. (2022). Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding. Proceedings of International Conference on Machine Learning. [arXiv] [summary] [slides] [code] [video]
    [BibTeX]
    @inproceedings{ttp_pairwise_22,
      year = {2022},
      booktitle = {Proceedings of International Conference on Machine Learning},
      archiveprefix = {arXiv},
      eprint = {2110.12650},
      primaryclass = {math.OC},
      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}
    }
  25. Wäldchen, S., Huber, F., and Pokutta, S. (2022). Training Characteristic Functions with Reinforcement Learning: XAI-methods Play Connect Four. Proceedings of International Conference on Machine Learning. [arXiv] [poster] [video]
    [BibTeX]
    @inproceedings{whp_connectfour_22,
      year = {2022},
      booktitle = {Proceedings of 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}
    }
  26. Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Approximately Vanishing Ideal. Proceedings of International Conference on Artificial Intelligence and Statistics. [arXiv] [summary] [poster] [code]
    [BibTeX]
    @inproceedings{wp_approxvanideal_22,
      year = {2022},
      booktitle = {Proceedings of 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}
    }
  27. Carderera, A., Besançon, M., and Pokutta, S. (2021). Simple Steps Are All You Need: Frank-Wolfe and Generalized Self-concordant Functions. Proceedings of Conference on Neural Information Processing Systems, 34, 5390–5401. [URL] [summary] [slides] [poster] [code]
    [BibTeX]
    @inproceedings{CBP2021:1,
      year = {2021},
      booktitle = {Proceedings of 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},
      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}
    }
  28. Chmiela, A., Khalil, E. B., Gleixner, A., Lodi, A., and Pokutta, S. (2021). Learning to Schedule Heuristics in Branch-and-bound. Proceedings of Conference on Neural Information Processing Systems, 34, 24235–24246. [URL] [arXiv] [poster]
    [BibTeX]
    @inproceedings{CKGLP2021,
      year = {2021},
      booktitle = {Proceedings of 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}
    }
  29. Carderera, A., Diakonikolas, J., Lin, C. Y., and Pokutta, S. (2021). Parameter-free Locally Accelerated Conditional Gradients. Proceedings of ICML. [arXiv] [slides]
    [BibTeX]
    @article{CDLP2021,
      arxiv = {https://arxiv.org/abs/2102.06806},
      author = {Carderera, Alejandro and Diakonikolas, Jelena and Lin, Cheuk Yin and Pokutta, Sebastian},
      month = feb,
      journal = {Proceedings of ICML},
      title = {{Parameter-free Locally Accelerated Conditional Gradients}},
      slides = {http://www.pokutta.com/slides/20210716_PF_LaCG_Poster.pdf},
      year = {2021}
    }
  30. Sofranac, B., Gleixner, A., and Pokutta, S. (2021). An Algorithm-independent Measure of Progress for Linear Constraint Propagation. Proceedings of International Conference on Principles and Practice of Constraint Programming, 52:1–17. DOI: 10.4230/LIPIcs.CP.2021.52 [URL] [arXiv] [video]
    [BibTeX]
    @inproceedings{SofranacGleixnerPokutta2022_AnAlgorithm-IndependentMeasure:1,
      year = {2021},
      booktitle = {Proceedings of 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}
    }
  31. Mortagy, H., Gupta, S., and Pokutta, S. (2020). Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization. Proceedings of NeurIPS. [arXiv] [slides] [poster] [code] [video]
    [BibTeX]
    @article{MGP2020walking,
      arxiv = {https://arxiv.org/abs/2006.08426},
      author = {Mortagy, Hassan and Gupta, Swati and Pokutta, Sebastian},
      code = {https://github.com/pokutta/Walking-in-the-Shadow},
      poster = {https://app.box.com/s/y266djezdjdidsswaopvdcnsnkp8774i},
      journal = {{Proceedings of NeurIPS}},
      slides = {https://app.box.com/s/wjhpe4nh8kv5pw6vl5jbp902v3mksivs},
      video = {https://youtu.be/CRmASevfnmE},
      title = {{Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization}},
      month = jun,
      year = {2020}
    }
  32. Combettes, C. W., and Pokutta, S. (2020). Boosting Frank-Wolfe by Chasing Gradients. Proceedings of ICML. [PDF] [arXiv] [summary] [slides] [code] [video]
    [BibTeX]
    @article{CP2020boost,
      annote = {github code: https://github.com/cyrillewcombettes/boostfw},
      arxiv = {http://arxiv.org/abs/2003.06369},
      author = {Combettes, Cyrille W and Pokutta, Sebastian},
      code = {https://colab.research.google.com/drive/1TSOVjDFF1X2ADBo_adHLsUVrblSutRKw},
      journal = {{Proceedings of ICML}},
      slides = {https://app.box.com/s/wwj247r5d456q0778p9b9y1jm6txuifb},
      summary = {http://www.pokutta.com/blog/research/2020/03/16/boostFW.html},
      title = {{Boosting Frank-Wolfe by Chasing Gradients}},
      pdfurl = {http://proceedings.mlr.press/v119/combettes20a.html},
      video = {https://www.youtube.com/watch?v=BfyV0C5FRbE},
      month = mar,
      year = {2020}
    }
  33. Sofranac, B., Gleixner, A., and Pokutta, S. (2020). Accelerating Domain Propagation: An Efficient GPU-parallel Algorithm Over Sparse Matrices. Proceedings of 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{SofranacGleixnerPokutta2022_Accelerating:1,
      year = {2020},
      booktitle = {Proceedings of 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}
    }
  34. Diakonikolas, J., Carderera, A., and Pokutta, S. (2020). Locally Accelerated Conditional Gradients. Proceedings of AISTATS. [PDF] [arXiv] [summary] [slides] [code] [video]
    [BibTeX]
    @article{CDP2019,
      arxiv = {https://arxiv.org/abs/1906.07867},
      author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian},
      code = {https://colab.research.google.com/drive/1ejjfCan7xnEhWWJXCIzb03CwQRG9iW_O},
      journal = {{Proceedings of AISTATS}},
      slides = {https://app.box.com/s/gphkhapso7d1vrfnzqykkb3vx0agxh8w},
      summary = {http://www.pokutta.com/blog/research/2019/07/04/LaCG-abstract.html},
      title = {{Locally Accelerated Conditional Gradients}},
      pdfurl = {http://proceedings.mlr.press/v108/diakonikolas20a/diakonikolas20a.pdf},
      year = {2020},
      video = {https://slideslive.com/38930107/locally-accelerated-conditional-gradients?ref=account-folder-52123-folders}
    }
  35. Braun, G., Pokutta, S., Tu, D., and Wright, S. (2019). Blended Conditional Gradients: the Unconditioning of Conditional Gradients. Proceedings of International Conference on Machine Learning, 97, 735–743. [URL] [arXiv] [summary] [slides] [poster] [code]
    [BibTeX]
    @inproceedings{Braun2018blendedCG,
      year = {2019},
      booktitle = {Proceedings of 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}
    }
  36. Diakonikolas, J., Carderera, A., and Pokutta, S. (2019). Breaking the Curse of Dimensionality (Locally) to Accelerate Conditional Gradients. OPTML Workshop Paper. [PDF] [arXiv] [summary] [slides] [poster] [code]
    [BibTeX]
    @article{CDPOPTML2019,
      arxiv = {https://arxiv.org/abs/1906.07867},
      author = {Diakonikolas, Jelena and Carderera, Alejandro and Pokutta, Sebastian},
      code = {https://colab.research.google.com/drive/1ejjfCan7xnEhWWJXCIzb03CwQRG9iW_O},
      journal = {{OPTML Workshop Paper}},
      pdfurl = {https://opt-ml.org/papers/2019/paper_26.pdf},
      poster = {https://app.box.com/s/d7p038u7df422q4jsccbmj15mngqv2ws},
      slides = {https://app.box.com/s/gphkhapso7d1vrfnzqykkb3vx0agxh8w},
      summary = {http://www.pokutta.com/blog/research/2019/07/04/LaCG-abstract.html},
      title = {{Breaking the Curse of Dimensionality (Locally) to Accelerate Conditional Gradients}},
      year = {2019}
    }
  37. Combettes, C. W., and Pokutta, S. (2019). Blended Matching Pursuit. Proceedings of NeurIPS. [PDF] [arXiv] [summary] [slides] [poster] [code]
    [BibTeX]
    @article{CP2019,
      arxiv = {https://arxiv.org/abs/1904.12335},
      author = {Combettes, Cyrille W and Pokutta, Sebastian},
      code = {https://colab.research.google.com/drive/17XYIxnCcJjKswba9mAaXFWnNGVZdsaXQ},
      journal = {{Proceedings of NeurIPS}},
      pdfurl = {https://papers.nips.cc/paper/8478-blended-matching-pursuit},
      poster = {https://app.box.com/s/j6lbh49udjd45krhxcypufxwdofw6br8},
      slides = {https://app.box.com/s/8lfktq6h3dqp9t2gqydu2tp8h2uxgz7m},
      summary = {http://www.pokutta.com/blog/research/2019/05/27/bmp-abstract.html},
      title = {{Blended Matching Pursuit}},
      year = {2019}
    }
  38. Braun, G., Pokutta, S., and Zink, D. (2017). Lazifying Conditional Gradient Algorithms. Proceedings of International Conference on Machine Learning, 70, 566–575. [URL] [arXiv] [slides] [poster]
    [BibTeX]
    @inproceedings{Braun2017lazyCG:1,
      year = {2017},
      booktitle = {Proceedings of 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}
    }
  39. Roy, A., Xu, H., and Pokutta, S. (2017). Reinforcement Learning under Model Mismatch. Proceedings of NIPS. [arXiv]
    [BibTeX]
    @article{AXP2016,
      annote = {https://papers.nips.cc/paper/by-source-2016-1199
      
      https://arxiv.org/abs/1610.09269
      
      },
      arxiv = {https://arxiv.org/abs/1706.04711},
      author = {Roy, Aurko and Xu, Huan and Pokutta, Sebastian},
      journal = {{Proceedings of NIPS}},
      title = {{Reinforcement Learning under Model Mismatch}},
      year = {2017}
    }
  40. Bärmann, A., Pokutta, S., and Schneider, O. (2017). Emulating the Expert: Inverse Optimization through Online Learning. Proceedings of the International Conference on Machine Learning (ICML). [PDF] [arXiv] [summary] [slides] [poster] [video]
    [BibTeX]
    @article{BPS2017,
      arxiv = {https://arxiv.org/abs/1810.12997},
      author = {B{\"a}rmann, Andreas and Pokutta, Sebastian and Schneider, Oskar},
      journal = {{Proceedings of the International Conference on Machine Learning (ICML)}},
      pdfurl = {http://proceedings.mlr.press/v70/barmann17a.html},
      poster = {https://app.box.com/s/h3ychkv99il7oyzw7sym8la5lhit3elg},
      slides = {https://app.box.com/s/7ti8sz8mf5s2znn1qo32in4jxy5gjnn1},
      summary = {http://www.pokutta.com/blog/research/2018/11/25/expertLearning-abstract.html},
      title = {{Emulating the Expert: Inverse Optimization through Online Learning}},
      video = {https://vimeo.com/channels/1301905/237243668},
      year = {2017}
    }
  41. Braun, G., Pokutta, S., and Roy, A. (2016). Strong Reductions for Extended Formulations. Proceedings of Conference on Integer Programming and Combinatorial Optimization, 9682, 350–361. DOI: 10.1007/978-3-319-33461-5_29 [arXiv]
    [BibTeX]
    @inproceedings{BPR2015:1,
      year = {2016},
      booktitle = {Proceedings of 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}
    }
  42. 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 Symposium on Discrete Algorithms, 1067–1078. DOI: 10.1137/1.9781611974331.ch75 [arXiv]
    [BibTeX]
    @inproceedings{Braun2016matching-symmetricSDP:1,
      year = {2016},
      booktitle = {Proceedings of 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}
    }
  43. Roy, A., and Pokutta, S. (2016). Hierarchical Clustering via Spreading Metrics. Proceedings of NIPS. [URL] [arXiv]
    [BibTeX]
    @article{AP2016,
      arxiv = {https://arxiv.org/abs/1610.09269},
      author = {Roy, Aurko and Pokutta, Sebastian},
      journal = {{Proceedings of NIPS}},
      url = {https://papers.nips.cc/paper/by-source-2016-1199},
      special = {{Oral Presentation + Conference Proceedings}},
      title = {{Hierarchical Clustering via Spreading Metrics}},
      year = {2016}
    }
  44. Braun, G., Pokutta, S., and Zink, D. (2015). Inapproximability of Combinatorial Problems Via Small LPs and SDPs. Proceedings of Annual Symposium on Theory of Computing, 107–116. DOI: 10.1145/2746539.2746550 [arXiv] [video]
    [BibTeX]
    @inproceedings{Braun2015LP-SDP:1,
      year = {2015},
      booktitle = {Proceedings of 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}
    }
  45. Braun, G., and Pokutta, S. (2015). The Matching Polytope Does Not Admit Fully-polynomial Size Relaxation Schemes. Proceedings of Symposium on Discrete Algorithms, 837–846. DOI: 10.1137/1.9781611973730.57 [arXiv]
    [BibTeX]
    @inproceedings{Braun2014matching,
      year = {2015},
      booktitle = {Proceedings of 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}
    }
  46. Braun, G., Firorini, S., and Pokutta, S. (2014). Average Case Polyhedral Complexity of the Maximum Stable Set Problem. Proceedings of Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 28, 515–530. DOI: 10.4230/LIPIcs.APPROX-RANDOM.2014.515 [URL] [arXiv]
    [BibTeX]
    @inproceedings{Braun2013stable:1,
      year = {2014},
      booktitle = {Proceedings of 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}
    }
  47. Braun, G., Pokutta, S., and Xie, Y. (2014). Info-greedy Sequential Adaptive Compressed Sensing. Proceedings of Allerton Conference on Communication, Control, and Computing (Allerton), 858–865. DOI: 10.1109/ALLERTON.2014.7028544 [arXiv]
    [BibTeX]
    @inproceedings{Braun2014info-greedy:1,
      year = {2014},
      booktitle = {Proceedings of 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}
    }
  48. Braun, G., and Pokutta, S. (2013). Common Information and Unique Disjointness. Proceedings of Annual Symposium on Foundations of Computer Science, 688–697. [URL]
    [BibTeX]
    @inproceedings{Braun2013info-disjoint:1,
      year = {2013},
      booktitle = {Proceedings of Annual 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}
    }
  49. Schmaltz, C., Pokutta, S., Heidorn, T., and Andrae, S. (2013). How to make regulators and shareholders happy under Basel III. Proceedings of the 26th Australasian Finance and Banking Conference. DOI: 10.1016/j.jbankfin.2014.05.031 [URL]
    [BibTeX]
    @article{basel2012,
      doi = {10.1016/j.jbankfin.2014.05.031},
      url = {http://ssrn.com/abstract=2179490},
      author = {Schmaltz, Christian and Pokutta, Sebastian and Heidorn, Thomas and Andrae, Silvio},
      journal = {{Proceedings of the 26th Australasian Finance and Banking Conference}},
      title = {{How to make regulators and shareholders happy under Basel III}},
      year = {2013}
    }
  50. Briët, J., Dadush, D., and Pokutta, S. (2013). On the existence of 0/1 polytopes with high semidefinite extension complexity. Proceedings of ESA. [arXiv]
    [BibTeX]
    @article{BDP2013,
      arxiv = {http://arxiv.org/abs/1305.3268},
      author = {Bri\"et, Jop and Dadush, Daniel and Pokutta, Sebastian},
      journal = {{Proceedings of ESA}},
      title = {{On the existence of 0/1 polytopes with high semidefinite extension complexity}},
      year = {2013}
    }
  51. Braun, G., and Pokutta, S. (2012). An Algebraic Approach to Symmetric Extended Formulations. Proceedings of International Symposium on Combinatorial Optimization, 7422, 141–152. DOI: 10.1007/978-3-642-32147-4_14 [arXiv]
    [BibTeX]
    @inproceedings{Braun2012symEF,
      year = {2012},
      booktitle = {Proceedings of 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}
    }
  52. Braun, G., Firorini, S., Pokutta, S., and Steurer, D. (2012). Approximation Limits of Linear Programs (beyond Hierarchies). Proceedings of Annual Symposium on Foundations of Computer Science, 480–489. DOI: 10.1109/FOCS.2012.10 [arXiv]
    [BibTeX]
    @inproceedings{Braun2012UDISJ:1,
      year = {2012},
      booktitle = {Proceedings of Annual Symposium on Foundations of Computer Science},
      pages = {480–489},
      doi = {10.1109/FOCS.2012.10},
      archiveprefix = {arXiv},
      eprint = {1204.0957},
      primaryclass = {c.CC},
      author = {Braun, Gábor and Firorini, Samuel and Pokutta, Sebastian and Steurer, David},
      title = {Approximation Limits of Linear Programs (beyond Hierarchies)}
    }
  53. Braun, G., and Pokutta, S. (2010). Rank of Random Half-integral Polytopes. Proceedings of Electronic Notes in Discrete Mathematics, 36, 415–422. DOI: 10.1016/j.endm.2010.05.053 [URL]
    [BibTeX]
    @inproceedings{Braun2011half:1,
      year = {2010},
      booktitle = {Proceedings of 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/DB_HTML/2010/11/2813.html},
      author = {Braun, Gábor and Pokutta, Sebastian},
      title = {Rank of Random Half-integral Polytopes}
    }

Full articles

  1. 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{fwshortintro2023,
      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}
    }
  2. Braun, G., Guzmán, C., and Pokutta, S. (2024). Corrigendum in “Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization Via Information Theory.” IEEE Transactions on Information Theory. DOI: 10.1109/TIT.2024.3357200
    [BibTeX]
    @article{Braun2013lowerCO_corr,
      year = {2024},
      journal = {IEEE Transactions on Information Theory},
      doi = {10.1109/TIT.2024.3357200},
      author = {Braun, Gábor and Guzmán, Cristóbal and Pokutta, Sebastian},
      title = {Corrigendum in “Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization Via Information Theory”}
    }
  3. Carderera, A., Besançon, M., and Pokutta, S. (2024). Scalable Frank-Wolfe on Generalized Self-concordant Functions Via Simple Steps. SIAM Journal on Optimization. [summary] [slides] [poster] [code]
    [BibTeX]
    @article{CBP2021,
      year = {2024},
      journal = {SIAM Journal on Optimization},
      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}
    }
  4. 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{dpp_geometric_scaling_22,
      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}
    }
  5. Mundinger, K., Pokutta, S., Spiegel, C., and Zimmer, M. (2024). Extending the Continuum of Six-Colorings. Geombinatorics Quarterly. [arXiv]
    [BibTeX]
    @article{mpsz_hadwigernelsonspectrum_24,
      year = {2024},
      journal = {Geombinatorics Quarterly},
      archiveprefix = {arXiv},
      eprint = {2404.05509},
      author = {Mundinger, Konrad and Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
      title = {Extending the Continuum of Six-Colorings}
    }
  6. Designolle, S., VĂ©rtesi, T., and Pokutta, S. (2024). Symmetric Multipartite Bell Inequalities Via Frank-Wolfe Algorithms. Physics Review A. [arXiv]
    [BibTeX]
    @article{symmetricBell2023,
      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}
    }
  7. 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{dibkgp_bell_23,
      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}
    }
  8. 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. [arXiv]
    [BibTeX]
    @article{abblpsst_distributionally_ro_23,
      year = {2023},
      journal = {INFORMS Journal on Optimization},
      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}
    }
  9. 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{abssmooth-fw_2023,
      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}
    }
  10. Bienstock, D., Muñoz, G., and Pokutta, S. (2023). Principled Deep Neural Network Training Through Linear Programming. Discrete Optimization. [URL] [arXiv] [summary]
    [BibTeX]
    @article{principledDNN_LP_2018,
      year = {2023},
      journal = {Discrete Optimization},
      url = {https://www.sciencedirect.com/science/article/abs/pii/S1572528623000373},
      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}
    }
  11. Combettes, C. W., 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 [PDF] [arXiv] [summary] [slides] [code] [video]
    [BibTeX]
    @article{cp2019approxCara,
      arxiv = {https://arxiv.org/abs/1911.04415},
      doi = {10.1007/s10107-021-01735-x},
      author = {Combettes, Cyrille W and Pokutta, Sebastian},
      code = {https://colab.research.google.com/drive/1GLGRTc2jFYy9CqqoVnZgIFVQgAC0c3aZ},
      journal = {Mathematical Programming A},
      volume = {197},
      pages = {191–-214},
      slides = {https://app.box.com/s/f0zuvr45qa6etidd06i1wart58o7bc8t},
      summary = {http://www.pokutta.com/blog/research/2019/11/30/approxCara-abstract.html},
      title = {{Revisiting the Approximate Carath{\'e}odory Problem via the Frank-Wolfe Algorithm}},
      video = {https://www.youtube.com/watch?v=VB1e0HrDmVo},
      pdfurl = {https://rdcu.be/cCnPL},
      year = {2023}
    }
  12. 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{besanccon2022frankwolfe,
      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}
    }
  13. 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{SofranacGleixnerPokutta2022_Accelerating,
      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}
    }
  14. 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{SofranacGleixnerPokutta2022_AnAlgorithm-IndependentMeasure,
      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}
    }
  15. Hunkenschröder, C., Pokutta, S., and Weismantel, R. (2022). Optimizing a Low-dimensional Convex Function Over a High-dimensional Cube. SIAM Journal on Optimization. [arXiv]
    [BibTeX]
    @article{hpw_lowhigh_22,
      year = {2022},
      journal = {SIAM Journal on Optimization},
      archiveprefix = {arXiv},
      eprint = {2204.05266},
      primaryclass = {math.OC},
      author = {Hunkenschröder, Christoph and Pokutta, Sebastian and Weismantel, Robert},
      title = {Optimizing a Low-dimensional Convex Function Over a High-dimensional Cube}
    }
  16. 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{khmbhhpshsgkff_22,
      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}
    }
  17. Faenza, Y., Muñoz, G., and Pokutta, S. (2022). New Limits of Treewidth-based tractability in Optimization. Mathematical Programming A, 191, 559–594. [PDF] [arXiv] [summary]
    [BibTeX]
    @article{FMP2018,
      arxiv = {https://arxiv.org/abs/1807.02551},
      author = {Faenza, Yuri and Mu{\~n}oz, Gonzalo and Pokutta, Sebastian},
      journal = {{Mathematical Programming A}},
      pdfurl = {http://link.springer.com/article/10.1007/s10107-020-01563-5},
      summary = {http://www.pokutta.com/blog/research/2018/09/22/treewidth-abstract.html},
      title = {{New Limits of Treewidth-based tractability in Optimization}},
      volume = {191},
      pages = {559--594},
      year = {2022}
    }
  18. Combettes, C. W., and Pokutta, S. (2021). Complexity of Linear Minimization and Projection on Some Sets. Operations Research Letters, 49(4). [arXiv] [code]
    [BibTeX]
    @article{CP2021,
      arxiv = {https://arxiv.org/abs/2101.10040},
      author = {Combettes, Cyrille W and Pokutta, Sebastian},
      code = {https://github.com/cyrillewcombettes/complexity},
      journal = {Operations Research Letters},
      month = jul,
      volume = {49},
      number = {4},
      title = {{Complexity of Linear Minimization and Projection on Some Sets}},
      year = {2021}
    }
  19. 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{KRAP2021,
      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}
    }
  20. 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{Braun2015LP-SDP,
      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}
    }
  21. 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{Braun2017lazyCG,
      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}
    }
  22. 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{BPR2015,
      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}
    }
  23. 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{Braun2016matching-symmetricSDP,
      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}
    }
  24. 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{Braun2013lowerCO,
      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}
    }
  25. 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{Braun2017info-nonnegative-rank,
      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}
    }
  26. Roy, A., and Pokutta, S. (2017). Hierarchical Clustering via Spreading Metrics. Journal of Machine Learning Research (JMLR), 18, 1–35. [URL] [arXiv]
    [BibTeX]
    @article{AP2016jour,
      annote = {https://papers.nips.cc/paper/by-source-2016-1199
      },
      arxiv = {https://arxiv.org/abs/1610.09269},
      author = {Roy, Aurko and Pokutta, Sebastian},
      journal = {{Journal of Machine Learning Research (JMLR)}},
      pages = {1--35},
      url = {http://jmlr.org/papers/v18/17-081.html},
      title = {{Hierarchical Clustering via Spreading Metrics}},
      volume = {18},
      year = {2017}
    }
  27. Bodur, M., Del Pia, A., Dey, S. S., Molinaro, M., and Pokutta, S. (2017). Aggregation-based cutting-planes for packing and covering Integer Programs. To Appear in Mathematical Programming A. DOI: 10.1007/s10107-017-1192-x [arXiv]
    [BibTeX]
    @article{BDDMP2016,
      doi = {10.1007/s10107-017-1192-x},
      arxiv = {http://arxiv.org/abs/1606.08951},
      author = {Bodur, Merve and Del~Pia, Alberto and Dey, Santanu~Sabush and Molinaro, Marco and Pokutta, Sebastian},
      journal = {to appear in Mathematical Programming A},
      title = {{Aggregation-based cutting-planes for packing and covering Integer Programs}},
      year = {2017}
    }
  28. 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{futMar2014,
      arxiv = {http://arxiv.org/abs/1404.6546},
      author = {Martin, Alexander and M{\"u}ller, J. and Pape, S. and Peter, A. and Pokutta, Sebastian and Winter, T.},
      journal = {{Mathematical Methods of Operations Research}},
      number = {2},
      pages = {155--177},
      title = {{Pricing and clearing combinatorial markets with singleton and swap orders}},
      volume = {85},
      year = {2017}
    }
  29. Gatzert, N., Pokutta, S., and Vogl, N. (2016+). Convergence of Capital and Insurance Markets: Pricing Aspects of Index-Linked Catastrophic Loss Instruments. To Appear in Journal of Risk and Insurance. [arXiv]
    [BibTeX]
    @article{gpv2013,
      arxiv = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2320370},
      author = {Gatzert, Nadine and Pokutta, Sebastian and Vogl, Nikolai},
      journal = {to appear in Journal of Risk and Insurance},
      title = {{Convergence of Capital and Insurance Markets: Pricing Aspects of Index-Linked Catastrophic Loss Instruments}},
      special = {{Best paper award at European Group of Risk and Insurance Economists Annual Meeting 2014 for conference version}},
      year = {2016+}
    }
  30. 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{Braun2013stable,
      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}
    }
  31. 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{Braun2013info-disjoint,
      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}
    }
  32. 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{Braun2009borderbaseis,
      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}
    }
  33. 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. [PDF] [arXiv]
    [BibTeX]
    @article{robopt2014,
      annote = {http://link.springer.com/article/10.1007/s10287-015-0243-0
      
      DOI:10.1007/s10287-015-0243-0},
      arxiv = {http://www.optimization-online.org/DB_HTML/2014/02/4245.html},
      author = {B{\"a}rmann, Andreas and Heidt, Andreas and Martin, Alexander and Pokutta, Sebastian and Thurner, Christoph},
      journal = {{Computational Management Science}},
      number = {2},
      pages = {151--193},
      pdfurl = {http://link.springer.com/article/10.1007/s10287-015-0243-0},
      title = {{Polyhedral Approximation of Ellipsoidal Uncertainty Sets via Extended Formulations - a computational case study}},
      volume = {13},
      year = {2016}
    }
  34. 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{Braun2012UDISJ,
      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 = {c.CC},
      author = {Braun, Gábor and Firorini, Samuel and Pokutta, Sebastian and Steurer, David},
      title = {Approximation Limits of Linear Programs (beyond Hierarchies)}
    }
  35. 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{Braun2014info-greedy,
      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}
    }
  36. Briët, 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{BDP2013jour,
      arxiv = {http://arxiv.org/abs/1305.3268},
      author = {Bri\"et, Jop and Dadush, Daniel and Pokutta, Sebastian},
      journal = {Mathematical Programming B},
      number = {1},
      pages = {179--199},
      title = {{On the existence of 0/1 polytopes with high semidefinite extension complexity}},
      volume = {153},
      year = {2015}
    }
  37. 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{Braun2012ChvatalGomory-compact,
      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}
    }
  38. 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. [PDF] [arXiv]
    [BibTeX]
    @article{basel2012jour,
      annote = {10.1016/j.jbankfin.2014.05.031},
      arxiv = {http://ssrn.com/abstract=2179490},
      author = {Schmaltz, Christian and Pokutta, Sebastian and Heidorn, Thomas and Andrae, Silvio},
      journal = {{Journal of Banking and Finance}},
      pages = {311--325},
      pdfurl = {http://dx.doi.org/10.1016/j.jbankfin.2014.05.031},
      title = {{How to make regulators and shareholders happy under Basel III}},
      year = {2014}
    }
  39. 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{Braun2011rigid,
      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}
    }
  40. 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{Braun2011half,
      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/DB_HTML/2010/11/2813.html},
      author = {Braun, Gábor and Pokutta, Sebastian},
      title = {Random Half-integral Polytopes}
    }

đź’¬ Talks and posters

Conference and workshop talks

Nov 2023
Workshop on Geometry and Machine Learning, Leipzig [PDF]
Sep 2023
7th Workshop on Future Algorithms and Applications, Berlin
Aug 2023
ICIAM 2023 Minisymposium: Advances in Optimization I, Tokyo [PDF]
Aug 2023
5th DOxML Conference, Tokyo [PDF]
Jul 2023
Jon-Shmuel Halfway to Twelfty [PDF]
View More / Less
Jun 2023
Lange Nacht Der Wissenschaften, Berlin
Mar 2023
ICERM Workshop: Combinatorics and Optimization, Providence [PDF]
Mar 2023
2nd Vienna Workshop on Computational Optimization, Vienna [PDF]
Mar 2023
Optimization and ML Workshop, Waischenfeld [PDF]
Dec 2022
Fields Workshop on Recent Advances in Optimization, Toronto [PDF]
Sep 2022
Advances in Classical and Quantum Algorithms for Optimiza..., Tokyo [PDF]
Jul 2022
Workshop on Algorithmic Optimization and Data Science, Trier [PDF]
Nov 2021
Oberwolfach Workshop on Combinatorial Optimization, Oberwolfach [PDF]
Oct 2021
HIM Workshop: Continuous Approaches to Discrete Optimization, Bonn [PDF]
Apr 2021
Google University Visit @ TU Berlin [PDF]
Feb 2021
IPAM Deep Learning and Combinatorial Optimization Workshop [PDF]
Nov 2020
Human-centric Artificial Intelligence: 2nd French-German-... [PDF]
Sep 2020
CPAIOR 2020 [PDF]
Sep 2020
CO@Work 2020 Summer School [PDF]
May 2020
MIP Workshop [PDF]
Mar 2020
Künstliche Intelligenz: Verständlich @ TH Wildau, Wildau [PDF]
Sep 2019
19th French-German-Swiss Conference on Optimization, Nice [PDF]
Sep 2019
Cargese Workshop on Combinatorial Optimization, Cargese [PDF]
Jan 2019
INFORMS Computing Society Conference, Knoxville [PDF]
Nov 2018
Hong Kong Analytics Community Meeting, Hong Kong [PDF]
Nov 2018
Oberwolfach Workshop on Combinatorial Optimization, Oberwolfach [PDF]
Apr 2018
Optimization and Discrete Geometry Workshop, Tel Aviv [PDF]

Research seminar talks

May 2023
University of Magdeburg MathCoRe Lecture, Magdeburg [PDF]
Apr 2023
Yale Statistics and Data Science Seminar Series, New Haven [PDF]
Mar 2023
Columbia IEOR Seminar Series, New York [PDF]
Apr 2022
IST ELLIS Seminar Series, Klosterneuburg [PDF]
Sep 2021
AI Campus Berlin Tech Lunch Talk [PDF]
View More / Less
May 2021
Math+ Friday Colloquium
Nov 2020
RWTH Aachen Mathematical Colloquium [PDF]
Jul 2019
Research Institute for Mathematical Sciences Seminar, Kyo..., Kyoto [PDF]