In Preparation / Articles Pending Review.
- Zimmer, M., Spiegel, C., and Pokutta, S. (2023). Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging. Preprint. [arXiv]
- Stengl, M., Gelß, P., Klus, S., and Pokutta, S. (2023). Existence and Uniqueness of Solutions of the Koopman–von Neumann Equation on Bounded Domains. Preprint. [arXiv]
- Deza, A., Onn, S., Pokutta, S., and Pournin, L. (2023). Kissing polytopes. Preprint. [arXiv]
- Martinez-Rubio, D., Roux, C., Criscitiello, C., and Pokutta, S. (2023). Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. Preprint. [arXiv]
- Kreimeier, T., Pokutta, S., Walther, A., and Woodstock, Z. (2023). On a Frank-Wolfe Approach for Abs-smooth Functions. Preprint. [arXiv]
- Braun, G., Pokutta, S., and Weismantel, R. (2022). Alternating Linear Minimization: Revisiting von Neumann’s alternating projections. Preprint. [arXiv] [slides] [video]
- Braun, G., Carderera, A., Combettes, C. W., Hassani, H., Karbasi, A., Mokthari, A., and Pokutta, S. (2022). Conditional Gradient Methods. Preprint. [arXiv]
- Hendrych, D., Troppens, H., Besançon, M., and Pokutta, S. (2022). Convex integer optimization with Frank-Wolfe methods. Preprint. [arXiv] [slides] [code]
- Parczyk, O., Pokutta, S., Spiegel, C., and Szabó, T. (2022). New Ramsey Multiplicity Bounds and Search Heuristics. Preprint. [arXiv] [slides]
- Wäldchen, S., Sharma, K., Zimmer, M., and Pokutta, S. (2022). Merlin-Arthur Classifiers: Formal Interpretability with Interactive Black Boxes. Preprint. [arXiv]
- Zimmer, M., Spiegel, C., and Pokutta, S. (2022). Compression-aware Training of Neural Networks using Frank-Wolfe. Preprint. [arXiv]
- Gelß, P., Klus, S., Shakibaei, Z., and Pokutta, S. (2022). Low-rank tensor decompositions of quantum circuits. Preprint. [arXiv]
- Deza, A., Pokutta, S., and Pournin, L. (2022). The complexity of geometric scaling. Preprint. [arXiv]
- Kerdreux, T., Scieur, D., d’Aspremont, A., and Pokutta, S. (2022). Strong Convexity of Feasible Sets in Riemannian Manifolds. Preprint.
- Roux, C., Wirth, E., Pokutta, S., and Kerdreux, T. (2021). Efficient Online-Bandit Strategies for Minimax Learning Problems. Preprint. [arXiv]
- Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2021). Local and Global Uniform Convexity Conditions. Preprint. [arXiv]
- 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]
- Pokutta, S., Spiegel, C., and Zimmer, M. (2020). Deep Neural Network Training with Frank-Wolfe. Preprint. [arXiv] [summary] [code]
- Combettes, C. W., Spiegel, C., and Pokutta, S. (2020). Projection-Free Adaptive Gradients for Large-Scale Optimization. Preprint. [arXiv] [summary] [code]
- Carderera, A., and Pokutta, S. (2020). Second-order Conditional Gradient Sliding. Preprint. [arXiv] [summary] [code]
- Bärmann, A., Martin, A., Pokutta, S., and Schneider, O. (2018). An Online-Learning Approach to Inverse Optimization. Submitted. [arXiv] [summary] [slides]
Refereed Conference Proceedings.
- Thuerck, D., Sofranac, B., Pfetsch, M., and Pokutta, S. (2023). Learning Cuts via Enumeration Oracles. To Appear in Proceedings of NeurIPS. [arXiv]
- Martinez-Rubio, D., Wirth, E., and Pokutta, S. (2023). Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond. Proceedings of COLT. [arXiv] [slides] [poster]
- Martinez-Rubio, D., and Pokutta, S. (2023). Accelerated Riemannian Optimization: Handling Constraints to Bound Geometric Penalties. Proceedings of COLT. [arXiv] [poster]
- Wirth, E., Kera, H., and Pokutta, S. (2023). Approximate Vanishing Ideal Computations at Scale. Proceedings of ICLR. [arXiv] [slides] [poster]
- Wirth, E., Kerdreux, T., and Pokutta, S. (2023). Acceleration of Frank-Wolfe algorithms with open loop step-sizes. Proceedings of AISTATS. [arXiv] [poster]
- Zimmer, M., Spiegel, C., and Pokutta, S. (2023). How I Learned to Stop Worrying and Love Retraining. Proceedings of ICLR. [arXiv] [poster] [code]
- Chmiela, A., Gleixner, A., Lichocki, P., and Pokutta, S. (2023). Online Learning for Scheduling MIP Heuristics. Proceedings of CPAIOR. [arXiv]
- Parczyk, O., Pokutta, S., Spiegel, C., and Szabó, T. (2022). Fully Computer-Assisted Proofs in Extremal Combinatorics. Proceedings of AAAI. [arXiv] [slides]
- Martinez-Rubio, D., and Pokutta, S. (2022). Accelerated Riemannian Optimization: Handling Constraints to Bound Geometric Penalties. NeurIPS OPT 2022 Workshop. [arXiv] [poster]
- Criado, F., Martinez-Rubio, D., and Pokutta, S. (2022). Fast Algorithms for Packing Proportional Fairness and its Dual. Proceedings of NeurIPS. [arXiv] [poster]
- Tsuji, K., Tanaka, K., and Pokutta, S. (2022). Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding. Proceedings of ICML. [arXiv] [summary] [slides] [code] [video]
- Wäldchen, S., Huber, F., and Pokutta, S. (2022). Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four. Proceedings of ICML. [arXiv] [poster] [video]
- Macdonald, J., Besançon, M., and Pokutta, S. (2022). Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings. Proceedings of ICML. [arXiv] [poster] [video]
- Gasse, M., 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., Morris, C., Papageorgiou, D. J., Parjadis, A., Pokutta, S., Prouvost, A., … Kun, M. (2022). The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. Proceedings of Machine Learning Research, 176, 220–231. [arXiv]
- Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Approximately Vanishing Ideal. Proceedings of AISTATS. [arXiv] [summary] [poster] [code]
- 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. [arXiv] [video]
- Carderera, A., Besançon, M., and Pokutta, S. (2021). Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions. Proceedings of NeurIPS. [arXiv] [summary] [slides] [poster] [code]
- Chmiela, A., Khalil, E., Gleixner, A., Lodi, A., and Pokutta, S. (2021). Learning to Schedule Heuristics in Branch-and-Bound. Proceedings of NeurIPS. [arXiv] [summary] [poster]
- Carderera, A., Diakonikolas, J., Lin, C. Y., and Pokutta, S. (2021). Parameter-free Locally Accelerated Conditional Gradients. Proceedings of ICML. [arXiv] [slides]
- Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2021). Projection-Free Optimization on Uniformly Convex Sets. Proceedings of AISTATS. [arXiv] [summary] [slides]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2020). Accelerating Domain Propagation: an Efficient GPU-Parallel Algorithm over Sparse Matrices. Proceedings of IA^3 at SC20. [arXiv] [summary] [slides] [video]
- Pokutta, S. (2020). Restarting Algorithms: Sometimes there is Free Lunch. Proceedings of CPAIOR. [arXiv] [slides] [video]
- 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]
- Combettes, C. W., and Pokutta, S. (2020). Boosting Frank-Wolfe by Chasing Gradients. Proceedings of ICML. [PDF] [arXiv] [summary] [slides] [code] [video]
- Pfetsch, M., and Pokutta, S. (2020). IPBoost – Non-Convex Boosting via Integer Programming. Proceedings of ICML. [arXiv] [summary] [slides] [code]
- Pokutta, S., Singh, M., and Torrico, A. (2020). On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. Proceedings of ICML. [arXiv] [summary] [slides] [poster] [video]
- Diakonikolas, J., Carderera, A., and Pokutta, S. (2020). Locally Accelerated Conditional Gradients. Proceedings of AISTATS. [PDF] [arXiv] [summary] [slides] [code] [video]
- Pokutta, S., Singh, M., and Torrico, A. (2019). On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness. OPTML Workshop Paper. [PDF] [summary] [poster]
- 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]
- Combettes, C. W., and Pokutta, S. (2019). Blended Matching Pursuit. Proceedings of NeurIPS. [PDF] [arXiv] [summary] [slides] [poster] [code]
- Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2019). Restarting Frank-Wolfe. Proceedings of AISTATS. [PDF] [arXiv] [summary] [slides]
- Anari, N., Haghtalab, N., Naor, S., Pokutta, S., Singh, M., and Torrico, A. (2019). Structured Robust Submodular Maximization: Offline and Online Algorithms. Proceedings of AISTATS. [PDF] [arXiv]
- Braun, G., Pokutta, S., Tu, D., and Wright, S. (2019). Blended Conditional Gradients: the unconditioning of conditional gradients. Proceedings of ICML. [PDF] [arXiv] [summary] [slides] [poster] [code]
- Inanlouganji, A., Pedrielli, G., Fainekos, G., and Pokutta, S. (2018). Continuous Simulation Optimization with Model Mismatch Using Gaussian Process Regression. Proceedings of the 2018 Winter Simulation Conference.
- Pokutta, S., Singh, M., and Torrico, A. (2018). Efficient algorithms for robust submodular maximization under matroid constraints. ICML Workshop Paper. [PDF] [arXiv]
- Braun, G., Pokutta, S., and Zink, D. (2017). Lazifying Conditional Gradient Algorithms. Proceedings of the International Conference on Machine Learning (ICML). [PDF] [arXiv] [slides] [poster]
- Roy, A., Xu, H., and Pokutta, S. (2017). Reinforcement Learning under Model Mismatch. Proceedings of NIPS. [arXiv]
- 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]
- Lan, G., Pokutta, S., Zhou, Y., and Zink, D. (2017). Conditional Accelerated Lazy Stochastic Gradient Descent. Proceedings of the International Conference on Machine Learning (ICML). [PDF] [arXiv] [poster]
- Arumugam, K., Kadampot, I., Tahmasbi, M., Shah, S., Bloch, M., and Pokutta, S. (2017). Modulation Recognition Using Side Information and Hybrid Learning. Proceedings of IEEE DySPAN.
- Braun, G., Roy, A., and Pokutta, S. (2016). Stronger Reductions for Extended Formulations. Proceedings of IPCO. [arXiv]
- Braun, G., Brown-Cohen, J., Huq, A., Pokutta, S., Raghavendra, P., Weitz, B., and Zink, D. (2016). The matching problem has no small symmetric SDP. Proceedings of SODA 2016. [PDF] [arXiv]
- Roy, A., and Pokutta, S. (2016). Hierarchical Clustering via Spreading Metrics. Proceedings of NIPS. [PDF] [arXiv]
- Xie, Y., Li, Q., and Pokutta, S. (2015). Supervised Online Subspace Tracking. Proceedings of Asilomar Conference on Signals, Systems, and Computers.
- Song, R., Xie, Y., and Pokutta, S. (2015). Sequential Sensing with Model Mismatch. Proceedings of ISIT.
- Braun, G., Pokutta, S., and Zink, D. (2015). Inapproximability of combinatorial problems via small LPs and SDPs. Proceeedings of STOC. [arXiv] [video]
- Pokutta, S. (2015). Information Theory and Polyhedral Combinatorics. Proceedings of 53rd Annual Allerton Conference on Communication, Control, and Computing. [PDF]
- Braun, G., and Pokutta, S. (2015). The matching polytope does not admit fully-polynomial size relaxation schemes. Proceeedings of SODA. [arXiv]
- Bazzi, A., Fiorini, S., Pokutta, S., and Svensson, O. (2015). Small linear programs cannot approximate Vertex Cover within a factor of 2 - epsilon. Proceedings of FOCS. [arXiv] [slides]
- Braun, G., Pokutta, S., and Xie, Y. (2014). Info-Greedy Sequential Adaptive Compressed Sensing. Proceedings of 52nd Annual Allerton Conference on Communication, Control, and Computing. [arXiv]
- Braun, G., Fiorini, S., and Pokutta, S. (2014). Average case polyhedral complexity of the maximum stable set problem. Proceedings of RANDOM. [PDF] [arXiv]
- Briët, J., Dadush, D., and Pokutta, S. (2013). On the existence of 0/1 polytopes with high semidefinite extension complexity. Proceedings of ESA. [arXiv]
- Braun, G., and Pokutta, S. (2013). Common information and unique disjointness. Foundations of Computer Science (FOCS), 2013 IEEE 54th Annual Symposium, 688–697. [arXiv]
- 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. [arXiv]
- Braun, G., and Pokutta, S. (2012). An algebraic view on symmetric extended formulations. Proceedings of ISCO, Lecture Notes in Computer Science, 7422(141–152). [arXiv]
- Braun, G., Fiorini, S., Pokutta, S., and Steurer, D. (2012). Approximation Limits of Linear Programs (Beyond Hierarchies). Proceedings of FOCS. [arXiv]
- Fiorini, S., Massar, S., Pokutta, S., Tiwary, H. R., and de Wolf, R. (2012). Linear vs. Semidefinite Extended Formulations: Exponential Separation and Strong Lower Bounds. Proceedings of STOC. [arXiv]
- Pokutta, S., and Schmaltz, C. (2011). Optimal Planning under Basel III Regulations. Proceedings of 24th Australasian Finance and Banking Conference. [arXiv]
- Dey, S. S., and Pokutta, S. (2011). Design and verify: a new scheme for generating cutting-planes. Proceedings of IPCO, Lecture Notes in Computer Science, 6655, 143–155. [arXiv]
- Helmke, H., Gluchshenko, O., Martin, A., Peter, A., Pokutta, S., and Siebert, U. (2011). Optimal Mixed-Mode Runway Scheduling. Proceedings of DACS. [arXiv]
- Pokutta, S., and Schmaltz, C. (2011). A network model for bank lending capacity. Proceedings of Systemic Risk, Basel III, Financial Stability and Regulation. [arXiv]
- Pokutta, S., and Schulz, A. S. (2010). On the rank of generic cutting-plane proof systems. Proceedings of IPCO, Lecture Notes in Computer Science, 6080, 450–463. [PDF] [arXiv]
- Martin, A., Müller, J., and Pokutta, S. (2010). On clearing coupled day-ahead electricity markets. Proceedings of 23rd Australasian Finance and Banking Conference. [arXiv]
- Braun, G., and Pokutta, S. (2010). Rank of random half-integral polytopes. Electronic Notes in Discrete Mathematics, 36, 415–422. [PDF] [arXiv]
- Drewes, S., and Pokutta, S. (2010). Geometric mean maximization in the presence of discrete decisions. Proceedings of 23rd Australasian Finance and Banking Conference.
- Drewes, S., and Pokutta, S. (2010). Cutting-planes for weakly-coupled 0/1 second order cone programs. Electronic Notes in Discrete Mathematics, 36, 735–742. [PDF] [arXiv]
- Pokutta, S., and Schmaltz, C. (2009). Optimal degree of centralization of liquidity management. Proceedings of 22nd Australasian Finance and Banking Conference. [arXiv]
Refereed Journals.
- 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. To Appear in Physical Reviews Research. [arXiv] [slides]
- Bienstock, D., Muñoz, G., and Pokutta, S. (2023+). Principled Deep Neural Network Training through Linear Programming. To Appear in Discrete Optimization. [PDF] [arXiv] [summary]
- Aigner, K., Bärmann, A., Braun, K., Liers, F., Pokutta, S., Schneider, O., Sharma, K., and Tschuppik, S. (2023). Data-driven Distributionally Robust Optimization over Time. To Appear in INFORMS Journal on Optimization. [arXiv]
- Combettes, C. W., and Pokutta, S. (2023). Revisiting the Approximate Carathéodory Problem via the Frank-Wolfe Algorithm. Mathematical Programming A, 197, 191—214. [PDF] [arXiv] [summary] [slides] [code] [video]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2022). Accelerating Domain Propagation: an Efficient GPU-Parallel Algorithm over Sparse Matrices. Parallel Computing, 109. [PDF] [arXiv] [summary] [slides] [video]
- Sofranac, B., Gleixner, A., and Pokutta, S. (2022). An Algorithm-Independent Measure of Progress for Linear Constraint Propagation. Constraints, 27, 432–455. [PDF] [arXiv] [video]
- 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. [PDF]
- Hunkenschröder, C., Pokutta, S., and Weismantel, R. (2022). Optimizing a low-dimensional convex function over a high-dimensional cube. To Appear in SIAM Journal on Optimization. [arXiv]
- 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. [PDF] [arXiv] [summary] [slides] [code]
- Kerdreux, T., d’Aspremont, A., and Pokutta, S. (2022). Restarting Frank-Wolfe: Faster Rates under Hölderian Error Bounds. Journal of Optimization Theory and Applications, 192, 799–829. [PDF] [arXiv] [summary] [slides]
- 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]
- Combettes, C. W., and Pokutta, S. (2021). Complexity of Linear Minimization and Projection on Some Sets. Operations Research Letters, 49(4). [arXiv] [code]
- Kerdreux, T., Roux, C., d’Aspremont, A., and Pokutta, S. (2021). Linear Bandits on Uniformly Convex Sets. Journal of Machine Learning Research (JMLR), 22(284), 1–23. [PDF] [arXiv] [summary]
- Anari, N., Haghtalab, N., Naor, S., Pokutta, S., Singh, M., and Torrico, A. (2021). Structured Robust Submodular Maximization: Offline and Online Algorithms. INFORMS Journal on Computing, 33(4), 1259–1684. [PDF] [arXiv]
- Gatzert, N., Pokutta, S., and Vogl, N. (2019). Convergence of Capital and Insurance Markets: Pricing Aspects of Index-Linked Catastrophic Loss Instruments. Journal of Risk and Insurance, 86, 39–72. [arXiv]
- Bazzi, A., Fiorini, S., Pokutta, S., and Svensson, O. (2019). Small linear programs cannot approximate Vertex Cover within a factor of 2 - epsilon. Mathematics of Operations Research, 44(1), 1–375. [arXiv] [slides]
- Braun, G., Pokutta, S., and Zink, D. (2019). Affine Reductions for LPs and SDPs. Mathematical Programming A, 173(1), 281–312. [PDF] [arXiv]
- Braun, G., Pokutta, S., and Zink, D. (2019). Lazifying Conditional Gradient Algorithms. Journal of Machine Learning Research (JMLR), 20(71), 1–42. [PDF] [arXiv] [slides]
- Bodur, M., Del Pia, A., Dey, S. S., Molinaro, M., and Pokutta, S. (2018). Aggregation-based cutting-planes for packing and covering Integer Programs. Mathematical Programming A, 171, 331–359. [PDF] [arXiv]
- Braun, G., Roy, A., and Pokutta, S. (2018). Stronger Reductions for Extended Formulations. Mathematical Programming B, 172, 591–620. [arXiv]
- Knueven, B., Ostrowski, J., and Pokutta, S. (2018). Detecting Almost Symmetries in Graphs. Mathematical Programming C, 10, 143–185. [PDF] [arXiv]
- Song, R., Xie, Y., and Pokutta, S. (2018). On the effect of model mismatch for sequential Info-Greedy Sensing. EURASIP Journal on Advances in Signal Processing. [PDF]
- Le Bodic, P., Pfetsch, M., Pavelka, J., and Pokutta, S. (2018). Solving MIPs via Scaling-based Augmentation. Discrete Optimization, 27, 1–25. [PDF] [arXiv]
- Christensen, H., Khan, A., Pokutta, S., and Tetali, P. (2017). Multidimensional Bin Packing and Other Related Problems: A survey. Computer Science Review, 24, 63–79. [PDF]
- Roy, A., and Pokutta, S. (2017). Hierarchical Clustering via Spreading Metrics. Journal of Machine Learning Research (JMLR), 18, 1–35. [PDF] [arXiv]
- Braun, G., Jain, R., Lee, T., and Pokutta, S. (2017). Information-theoretic approximations of the nonnegative rank. Computational Complexity, 26(1), 147–197. [arXiv]
- 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]
- Braun, G., Guzmán, C., and Pokutta, S. (2017). Unifying Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization. IEEE Transactions of Information Theory, 63(7), 4709–4724. [PDF] [arXiv]
- Braun, G., Brown-Cohen, J., Huq, A., Pokutta, S., Raghavendra, P., Weitz, B., and Zink, D. (2017). The matching problem has no small symmetric SDP. Mathematical Programming A, 165(2), 643–662. [PDF] [arXiv]
- 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]
- Braun, G., Fiorini, S., and Pokutta, S. (2016). Average case polyhedral complexity of the maximum stable set problem. Mathematical Programming A, 160(1), 407–431. [PDF] [arXiv]
- Braun, G., and Pokutta, S. (2016). Common information and unique disjointness. Algorithmica, 76(3), 597–629. [PDF] [arXiv]
- Braun, G., and Pokutta, S. (2016). A polyhedral characterization of Border Bases. SIAM Journal on Discrete Mathematics, 30(1), 239–265. [arXiv]
- Braun, G., and Pokutta, S. (2015). The matching polytope does not admit fully-polynomial size relaxation schemes. IEEE Transactions on Information Theory, 61(10), 1–11. [PDF] [arXiv]
- Braun, G., Fiorini, S., Pokutta, S., and Steurer, D. (2015). Approximation Limits of Linear Programs (Beyond Hierarchies). Mathematics of Operations Research, 40(3), 179–199. [arXiv]
- 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]
- Fiorini, S., Massar, S., Pokutta, S., Tiwary, H. R., and de Wolf, R. (2015). Exponential Lower Bounds for Polytopes in Combinatorial Optimization. Journal of the ACM, 62(2), 1–17. [PDF] [arXiv]
- 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. [arXiv]
- Drewes, S., and Pokutta, S. (2014). Symmetry-exploiting cuts for a class of mixed-0/1 second order cone programs. Discrete Optimization, 13, 23–35. [arXiv]
- Drewes, S., and Pokutta, S. (2014). Computing discrete expected utility maximizing portfolios. Journal of Investing, 23(4), 121–132. [arXiv]
- 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]
- 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, 307–310. [arXiv]
- Martin, A., Müller, J., and Pokutta, S. (2014). Strict linear prices in non-convex European day-ahead electricity markets. Optimization Methods and Software, 29(1), 189–221. [PDF] [arXiv]
- Dey, S. S., and Pokutta, S. (2014). Design and verify: a new scheme for generating cutting-planes. Mathematical Programming A, 145, 199–222. [arXiv]
- Kroll, C., and Pokutta, S. (2013). Just a perfect day: developing a happiness optimised day schedule. Journal of Economic Psychology, 34, 210–217. [PDF] [video]
- Pokutta, S., and Van Vyve, M. (2013). A note on the extension complexity of the knapsack polytope. Operations Research Letters, 41, 347–350. [PDF] [arXiv]
- Pokutta, S., and Schmaltz, C. (2012). Optimal Planning under Basel III Regulations. Cass-Capco Institute Paper Series on Risk, 34. [PDF] [arXiv]
- Braun, G., and Pokutta, S. (2012). Rigid abelian groups and the probabilistic method. Contemporary Mathematics, 576, 17–30. [PDF] [arXiv]
- Göbel, R., and Pokutta, S. (2012). Absolutely rigid fields and Shelah’s absolutely rigid trees. Contemporary Mathematics, 576, 105–128. [PDF] [arXiv]
- Braun, G., and Pokutta, S. (2011). Random half-integral polytopes. Operations Research Letters, 39(3), 204–207. [arXiv]
- Haus, U. U., Hemmecke, R., and Pokutta, S. (2011). Reconstructing biochemical cluster networks. Journal of Mathematical Chemistry, 49(10), 2441–2456. [PDF] [arXiv]
- Letchford, A. N., Pokutta, S., and Schulz, A. S. (2011). On the membership problem for the 0,1/2-closure. Operations Research Letters, 39(5), 301–304. [PDF] [arXiv]
- Pokutta, S., and Schmaltz, C. (2011). Managing liquidity: Optimal degree of centralization. Journal of Banking and Finance, 35, 627–638. [PDF] [arXiv]
- Pokutta, S., and Schulz, A. S. (2011). Integer-empty polytopes in the 0/1-cube with maximal Gomory-Chvátal rank. Operations Research Letters, 39(6), 457–460. [PDF] [arXiv]
- Pokutta, S., and Stauffer, G. (2011). Lower bounds for the Chvátal-Gomory rank in the 0/1 cube. Operations Research Letters, 39(3), 200–203. [PDF] [arXiv]
- Pokutta, S., and Stauffer, G. (2009). France Telecom Workforce Scheduling Problem: a challenge. RAIRO-Operations Research, 43, 375–386. [PDF]
- Heldt, D., Kreuzer, M., Pokutta, S., and Poulisse, H. (2009). Approximate Computation of zero-dimensional polynomial ideals. Journal of Symbolic Computation, 44, 1566–1591. [PDF]
- Droste, M., Göbel, R., and Pokutta, S. (2008). Absolute graphs with prescribed endomorphism monoid. Semigroup Forum, 76, 256–267. [PDF]
- Göbel, R., and Pokutta, S. (2008). Construction of dual modules using Martin’s axiom. Journal of Algebra, 320, 2388–2404. [PDF]
- Pokutta, S., and Strüngmann, L. (2007). The Chase radical and reduced products. Journal of Pure and Applied Algebra, 211, 532–540. [PDF]
Unpublished Manuscripts.
- Braun, G., and Pokutta, S. (2021). Dual Prices for Frank-Wolfe Algorithms. Preprint. [arXiv]
- Pokutta, S., and Xu, H. (2021). Adversaries in Online Learning Revisited: with applications in Robust Optimization and Adversarial training. Preprint. [arXiv]
- Braun, G., and Pokutta, S. (2016). An efficient high-probability algorithm for Linear Bandits. Preprint. [arXiv]
- Braun, G., and Pokutta, S. (2015). An information diffusion Fano inequality. Preprint. [arXiv]
- Pokutta, S., and Schulz, A. S. (2013). On the rank of cutting-plane proof systems. Preprint. [arXiv]
- Braun, G., and Pokutta, S. (2012). An algebraic view on symmetric extended formulations. Preprint. [arXiv]
- Pokutta, S. (2011). Lower bounds for Chvátal-Gomory style operators. Preprint. [arXiv]
- Pokutta, S., Schmaltz, C., and Stiller, S. (2011). Measuring Systemic Risk and Contagion in Financial Networks. Preprint. [arXiv]
- Pokutta, S., and Schulz, A. S. (2009). On the connection of the Sherali-Adams closure and border bases. Preprint. [arXiv]
- Pokutta, S. (2008). Stowage optimization for inland vessels. Preprint.
Other.
- Pokutta, S. (2021). Mathematik, Machine Learning und Artificial Intelligence. To Appear in Mitteilungen Der DMV (German). [PDF]
- Lee, D., and Pokutta, S. (2015). Toward a Science of Autonomy for Physical Systems: Transportation. Computing Community Consortium White Paper. [PDF]
- Alf, M., and Pokutta, S. (2006). How logistics service providers can make use of the real options concept. Symposium Mathematik & Logistik, Bad Honnef 2005, Conference Proceedings.
- Heldt, D., Kreuzer, M., Pokutta, S., and Poulisse, H. (2006). Algebraische Modellierung mit Methoden der approximativen Computer Algebra und Anwendungen in der Ölindustrie. OR News, 15–18.
- Pokutta, S. (2005). Products over countable domains [PhD thesis]. In PhD thesis. University of Duisburg-Essen.
- Pokutta, S., and Törner, G. (2005). Fixpunktminimierung bei Binnenschiffen. OR News, 23, 13–17.
- Pokutta, S. (2003). Generalizations of the Chase radical and direct products [Master's thesis]. In Diploma thesis. University of Duisburg-Essen.