Sebastian Pokutta

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 127

Top Venues

Publications

Deborah Hendrych, Mathieu Besançon, Sebastian Pokutta
Solving the Optimal Experiment Design Problem with Mixed-Integer Convex Methods. SEA (2024)
Konrad Mundinger, Max Zimmer, Sebastian Pokutta
Neural Parameter Regression for Explicit Representations of PDE Solution Operators. CoRR (2024)
Jan Pauls, Max Zimmer, Una M. Kelly, Martin Schwartz, Sassan Saatchi, Philippe Ciais, Sebastian Pokutta, Martin Brandt, Fabian Gieseke
Estimating Canopy Height at Scale. CoRR (2024)
Stephan Wäldchen, Kartikey Sharma, Berkant Turan, Max Zimmer, Sebastian Pokutta
Interpretability Guarantees with Merlin-Arthur Classifiers. AISTATS (2024)
Gábor Braun, Cristóbal Guzmán, Sebastian Pokutta
Corrections to "Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory". IEEE Trans. Inf. Theory 70 (7) (2024)
Antoine Deza, Sebastian Pokutta, Lionel Pournin
The complexity of geometric scaling. Oper. Res. Lett. 52 (2024)
Christophe Roux, Max Zimmer, Sebastian Pokutta
On the Byzantine-Resilience of Distillation-Based Federated Learning. CoRR (2024)
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging. ICLR (2024)
Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta
Scalable Frank-Wolfe on Generalized Self-Concordant Functions via Simple Steps. SIAM J. Optim. 34 (3) (2024)
Daniel Bienstock, Gonzalo Muñoz, Sebastian Pokutta
Principled deep neural network training through linear programming. Discret. Optim. 49 (2023)
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging. CoRR (2023)
Elias Samuel Wirth, Thomas Kerdreux, Sebastian Pokutta
Acceleration of Frank-Wolfe Algorithms with Open-Loop Step-Sizes. AISTATS (2023)
David Martínez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. CoRR (2023)
David Martínez-Rubio, Sebastian Pokutta
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. COLT (2023)
Max Zimmer, Megi Andoni, Christoph Spiegel, Sebastian Pokutta
PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs. CoRR (2023)
Olaf Parczyk, Sebastian Pokutta, Christoph Spiegel, Tibor Szabó
Fully Computer-Assisted Proofs in Extremal Combinatorics. AAAI (2023)
Christoph Hunkenschröder, Sebastian Pokutta, Robert Weismantel
Minimizing a Low-Dimensional Convex Function Over a High-Dimensional Cube. SIAM J. Optim. 33 (2) (2023)
Shpresim Sadiku, Moritz Wagner, Sebastian Pokutta
Group-wise Sparse and Explainable Adversarial Attacks. CoRR (2023)
Daniel Thuerck, Boro Sofranac, Marc E. Pfetsch, Sebastian Pokutta
Learning Cuts via Enumeration Oracles. NeurIPS (2023)
Cyrille W. Combettes, Sebastian Pokutta
Revisiting the approximate Carathéodory problem via the Frank-Wolfe algorithm. Math. Program. 197 (1) (2023)
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
How I Learned to Stop Worrying and Love Retraining. ICLR (2023)
Elias Samuel Wirth, Hiroshi Kera, Sebastian Pokutta
Approximate Vanishing Ideal Computations at Scale. ICLR (2023)
Kevin-Martin Aigner, Andreas Bärmann, Kristin Braun, Frauke Liers, Sebastian Pokutta, Oskar Schneider, Kartikey Sharma, Sebastian Tschuppik
Data-Driven Distributionally Robust Optimization over Time. INFORMS J. Optim. 5 (4) (2023)
David Martínez-Rubio, Elias Samuel Wirth, Sebastian Pokutta
Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond. COLT (2023)
Antonia Chmiela, Ambros M. Gleixner, Pawel Lichocki, Sebastian Pokutta
Online Learning for Scheduling MIP Heuristics. CPAIOR (2023)
Antonia Chmiela, Ambros M. Gleixner, Pawel Lichocki, Sebastian Pokutta
Online Learning for Scheduling MIP Heuristics. CoRR (2023)
Deborah Hendrych, Hannah Troppens, Mathieu Besançon, Sebastian Pokutta
Convex integer optimization with Frank-Wolfe methods. CoRR (2022)
Boro Sofranac, Ambros M. Gleixner, Sebastian Pokutta
Accelerating domain propagation: An efficient GPU-parallel algorithm over sparse matrices. Parallel Comput. 109 (2022)
Yuri Faenza, Gonzalo Muñoz, Sebastian Pokutta
New limits of treewidth-based tractability in optimization. Math. Program. 191 (2) (2022)
Tabea Kossen, Manuel A. Hirzel, Vince I. Madai, Franziska Boenisch, Anja Hennemuth, Kristian Hildebrand, Sebastian Pokutta, Kartikey Sharma, Adam Hilbert, Jan Sobesky, Ivana Galinovic, Ahmed A. Khalil, Jochen B. Fiebach, Dietmar Frey
Toward Sharing Brain Images: Differentially Private TOF-MRA Images With Segmentation Labels Using Generative Adversarial Networks. Frontiers Artif. Intell. 5 (2022)
Mathieu Besançon, Alejandro Carderera, Sebastian Pokutta
FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank-Wolfe Algorithms and Conditional Gradients. INFORMS J. Comput. 34 (5) (2022)
Francisco Criado, David Martínez-Rubio, Sebastian Pokutta
Fast Algorithms for Packing Proportional Fairness and its Dual. NeurIPS (2022)
Stephan Wäldchen, Felix Huber, Sebastian Pokutta
Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four. CoRR (2022)
Elias Samuel Wirth, Sebastian Pokutta
Conditional Gradients for the Approximately Vanishing Ideal. AISTATS (2022)
Jan MacDonald, Mathieu Besançon, Sebastian Pokutta
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings. ICML (2022)
Elias Samuel Wirth, Hiroshi Kera, Sebastian Pokutta
Approximate Vanishing Ideal Computations at Scale. CoRR (2022)
Kazuma Tsuji, Ken'ichiro Tanaka, Sebastian Pokutta
Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding. ICML (2022)
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
Compression-aware Training of Neural Networks using Frank-Wolfe. CoRR (2022)
David Martínez-Rubio, Sebastian Pokutta
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties. CoRR (2022)
Maxime Gasse, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias B. Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yangm, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Chen Binbin, He Minggui, Hao Hao, Zhang Zhiyu, An Zhiwu, Mao Kun
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. CoRR (2022)
Elias Samuel Wirth, Sebastian Pokutta
Conditional Gradients for the Approximately Vanishing Ideal. CoRR (2022)
Stephan Wäldchen, Sebastian Pokutta, Felix Huber
Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four. ICML (2022)
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Restarting Frank-Wolfe: Faster Rates under Hölderian Error Bounds. J. Optim. Theory Appl. 192 (3) (2022)
Christoph Hunkenschröder, Sebastian Pokutta, Robert Weismantel
Optimizing a low-dimensional convex function over a high-dimensional cube. CoRR (2022)
Boro Sofranac, Ambros M. Gleixner, Sebastian Pokutta
An algorithm-independent measure of progress for linear constraint propagation. Constraints An Int. J. 27 (4) (2022)
Stephan Wäldchen, Kartikey Sharma, Max Zimmer, Sebastian Pokutta
Merlin-Arthur Classifiers: Formal Interpretability with Interactive Black Boxes. CoRR (2022)
Thomas Kerdreux, Christophe Roux, Alexandre d'Aspremont, Sebastian Pokutta
Linear Bandits on Uniformly Convex Sets. J. Mach. Learn. Res. 22 (2021)
Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions. CoRR (2021)
Antonia Chmiela, Elias B. Khalil, Ambros M. Gleixner, Andrea Lodi, Sebastian Pokutta
Learning to Schedule Heuristics in Branch-and-Bound. CoRR (2021)
Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions. NeurIPS (2021)
Boro Sofranac, Ambros M. Gleixner, Sebastian Pokutta
An Algorithm-Independent Measure of Progress for Linear Constraint Propagation. CP (2021)
Thomas Kerdreux, Christophe Roux, Alexandre d'Aspremont, Sebastian Pokutta
Linear Bandits on Uniformly Convex Sets. CoRR (2021)
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Local and Global Uniform Convexity Conditions. CoRR (2021)
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Projection-Free Optimization on Uniformly Convex Sets. AISTATS (2021)
Cyrille W. Combettes, Sebastian Pokutta
Complexity of Linear Minimization and Projection on Some Sets. CoRR (2021)
Antonia Chmiela, Elias Khalil, Ambros M. Gleixner, Andrea Lodi, Sebastian Pokutta
Learning to Schedule Heuristics in Branch and Bound. NeurIPS (2021)
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
Back to Basics: Efficient Network Compression via IMP. CoRR (2021)
Sebastian Pokutta, Huan Xu
Adversaries in Online Learning Revisited: with applications in Robust Optimization and Adversarial training. CoRR (2021)
Alfredo Torrico, Mohit Singh, Sebastian Pokutta, Nika Haghtalab, Joseph (Seffi) Naor, Nima Anari
Structured Robust Submodular Maximization: Offline and Online Algorithms. INFORMS J. Comput. 33 (4) (2021)
Maxime Gasse, Simon Bowly, Quentin Cappart, Jonas Charfreitag, Laurent Charlin, Didier Chételat, Antonia Chmiela, Justin Dumouchelle, Ambros M. Gleixner, Aleksandr M. Kazachkov, Elias Khalil, Pawel Lichocki, Andrea Lodi, Miles Lubin, Chris J. Maddison, Christopher Morris, Dimitri J. Papageorgiou, Augustin Parjadis, Sebastian Pokutta, Antoine Prouvost, Lara Scavuzzo, Giulia Zarpellon, Linxin Yang, Sha Lai, Akang Wang, Xiaodong Luo, Xiang Zhou, Haohan Huang, Sheng Cheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan, Zixuan Cao, Yang Xu, Zhewei Huang, Shuchang Zhou, Binbin Chen, Minggui He, Hao Hao, Zhiyu Zhang, Zhiwu An, Kun Mao
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. NeurIPS (Competition and Demos) (2021)
Christophe Roux, Elias Samuel Wirth, Sebastian Pokutta, Thomas Kerdreux
Efficient Online-Bandit Strategies for Minimax Learning Problems. CoRR (2021)
Jan MacDonald, Mathieu Besançon, Sebastian Pokutta
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings. CoRR (2021)
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
Parameter-free Locally Accelerated Conditional Gradients. CoRR (2021)
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
Parameter-free Locally Accelerated Conditional Gradients. ICML (2021)
Cyrille W. Combettes, Sebastian Pokutta
Complexity of linear minimization and projection on some sets. Oper. Res. Lett. 49 (4) (2021)
Cyrille W. Combettes, Sebastian Pokutta
Boosting Frank-Wolfe by Chasing Gradients. ICML (2020)
Hassan Mortagy, Swati Gupta, Sebastian Pokutta
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization. NeurIPS (2020)
Alejandro Carderera, Sebastian Pokutta
Second-order Conditional Gradients. CoRR (2020)
Boro Sofranac, Ambros M. Gleixner, Sebastian Pokutta
Accelerating Domain Propagation: an Efficient GPU-Parallel Algorithm over Sparse Matrices. CoRR (2020)
Sebastian Pokutta, Mohit Singh, Alfredo Torrico
On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. ICML (2020)
Alfredo Torrico, Mohit Singh, Sebastian Pokutta
On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. CoRR (2020)
Cyrille W. Combettes, Christoph Spiegel, Sebastian Pokutta
Projection-Free Adaptive Gradients for Large-Scale Optimization. CoRR (2020)
Hassan Mortagy, Swati Gupta, Sebastian Pokutta
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization. CoRR (2020)
Cyrille W. Combettes, Sebastian Pokutta
Boosting Frank-Wolfe by Chasing Gradients. CoRR (2020)
Boro Sofranac, Ambros M. Gleixner, Sebastian Pokutta
Accelerating Domain Propagation: An Efficient GPU-Parallel Algorithm over Sparse Matrices. IA3@SC (2020)
Marc E. Pfetsch, Sebastian Pokutta
IPBoost - Non-Convex Boosting via Integer Programming. CoRR (2020)
Marc E. Pfetsch, Sebastian Pokutta
IPBoost - Non-Convex Boosting via Integer Programming. ICML (2020)
Sebastian Pokutta, Christoph Spiegel, Max Zimmer
Deep Neural Network Training with Frank-Wolfe. CoRR (2020)
Sebastian Pokutta
Restarting Algorithms: Sometimes There Is Free Lunch. CPAIOR (2020)
Jelena Diakonikolas, Alejandro Carderera, Sebastian Pokutta
Locally Accelerated Conditional Gradients. AISTATS (2020)
Cyrille W. Combettes, Sebastian Pokutta
Revisiting the Approximate Carathéodory Problem via the Frank-Wolfe Algorithm. CoRR (2019)
Gábor Braun, Sebastian Pokutta, Daniel Zink
Lazifying Conditional Gradient Algorithms. J. Mach. Learn. Res. 20 (2019)
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Restarting Frank-Wolfe. AISTATS (2019)
Alejandro Carderera, Jelena Diakonikolas, Sebastian Pokutta
Locally Accelerated Conditional Gradients. CoRR (2019)
Gábor Braun, Sebastian Pokutta, Dan Tu, Stephen J. Wright
Blended Conditonal Gradients. ICML (2019)
Nima Anari, Nika Haghtalab, Seffi Naor, Sebastian Pokutta, Mohit Singh, Alfredo Torrico
Structured Robust Submodular Maximization: Offline and Online Algorithms. AISTATS (2019)
Cyrille W. Combettes, Sebastian Pokutta
Blended Matching Pursuit. CoRR (2019)
Cyrille W. Combettes, Sebastian Pokutta
Blended Matching Pursuit. NeurIPS (2019)
Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola Svensson
. Math. Oper. Res. 44 (1) (2019)
Gábor Braun, Sebastian Pokutta, Daniel Zink
Affine reductions for LPs and SDPs. Math. Program. 173 (1-2) (2019)
Merve Bodur, Alberto Del Pia, Santanu S. Dey, Marco Molinaro, Sebastian Pokutta
Aggregation-based cutting-planes for packing and covering integer programs. Math. Program. 171 (1-2) (2018)
Gábor Braun, Sebastian Pokutta, Dan Tu, Stephen J. Wright
Blended Conditional Gradients: the unconditioning of conditional gradients. CoRR (2018)
Daniel Bienstock, Gonzalo Muñoz, Sebastian Pokutta
Principled Deep Neural Network Training through Linear Programming. CoRR (2018)
Andreas Bärmann, Alexander Martin, Sebastian Pokutta, Oskar Schneider
An Online-Learning Approach to Inverse Optimization. CoRR (2018)
Pierre Le Bodic, Jeffrey William Pavelka, Marc E. Pfetsch, Sebastian Pokutta
Solving MIPs via scaling-based augmentation. Discret. Optim. 27 (2018)
Gábor Braun, Sebastian Pokutta, Aurko Roy
Strong reductions for extended formulations. Math. Program. 172 (1-2) (2018)
Ben Knueven, Jim Ostrowski, Sebastian Pokutta
Detecting almost symmetries of graphs. Math. Program. Comput. 10 (2) (2018)
Yuri Faenza, Gonzalo Muñoz, Sebastian Pokutta
Limits of Treewidth-based tractability in Optimization. CoRR (2018)
Ruiyang Song, Yao Xie, Sebastian Pokutta
On the effect of model mismatch for sequential Info-Greedy Sensing. EURASIP J. Adv. Signal Process. 2018 (2018)
Alireza Inanlouganji, Giulia Pedrielli, Georgios Fainekos, Sebastian Pokutta
Continuous simulation Optimization with Model mismatch using Gaussian Process Regression. WSC (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sebastian Pokutta