TY - CHAP A1 - Zimmer, Max A1 - Spiegel, Christoph A1 - Pokutta, Sebastian T1 - How I Learned to Stop Worrying and Love Retraining T2 - Proceedings of International Conference on Learning Representations Y1 - 2023 ER - TY - CHAP A1 - Mundinger, Konrad A1 - Zimmer, Max A1 - Kiem, Aldo A1 - Spiegel, Christoph A1 - Pokutta, Sebastian T1 - Neural Discovery in Mathematics: Do Machines Dream of Colored Planes? T2 - Proceedings of the 42nd International Conference on Machine Learning Y1 - 2025 UR - https://raw.githubusercontent.com/mlresearch/v267/main/assets/mundinger25a/mundinger25a.pdf VL - 267 SP - 45236 EP - 45255 ER - TY - JOUR A1 - Parczyk, Olaf A1 - Pokutta, Sebastian A1 - Spiegel, Christoph A1 - Szabó, Tibor T1 - New Ramsey multiplicity bounds and search heuristics JF - Foundations of Computational Mathematics Y1 - 2024 U6 - https://doi.org/10.1007/s10208-024-09675-6 ER - TY - CHAP A1 - Kiem, Aldo A1 - Pokutta, Sebastian A1 - Spiegel, Christoph T1 - Categorification of Flag Algebras T2 - Discrete Mathematics Days 2024 Y1 - 2024 U6 - https://doi.org/10.37536/TYSP5643 SP - 259 EP - 264 ER - TY - CHAP A1 - Kiem, Aldo A1 - Pokutta, Sebastian A1 - Spiegel, Christoph T1 - The Four-Color Ramsey Multiplicity of Triangles T2 - Discrete Mathematics Days 2024 Y1 - 2024 U6 - https://doi.org/10.37536/TYSP5643 SP - 13 EP - 18 ER - TY - JOUR A1 - Mundinger, Konrad A1 - Pokutta, Sebastian A1 - Spiegel, Christoph A1 - Zimmer, Max T1 - Extending the Continuum of Six-Colorings JF - Geombinatorics Quarterly Y1 - 2024 VL - 34 IS - 1 SP - 20 EP - 29 ER - TY - CHAP A1 - Mundinger, Konrad A1 - Pokutta, Sebastian A1 - Spiegel, Christoph A1 - Zimmer, Max T1 - Extending the Continuum of Six-Colorings T2 - Discrete Mathematics Days 2024 Y1 - 2024 U6 - https://doi.org/10.37536/TYSP5643 SP - 178 EP - 183 ER - TY - CHAP A1 - Zimmer, Max A1 - Spiegel, Christoph A1 - Pokutta, Sebastian T1 - Sparse Model Soups T2 - 12th International Conference on Learning Representations (ICLR 2024) Y1 - 2024 SN - 9781713898658 PB - Curran Associates, Inc. ER - TY - CHAP A1 - Rué Perna, Juanjo A1 - Spiegel, Christoph T1 - The Rado Multiplicity Problem in Vector Spaces Over Finite Fields T2 - Proceedings of the 12th European Conference on Combinatorics, Graph Theory and Applications, EUROCOMB’23 Y1 - 2023 U6 - https://doi.org/10.5817/CZ.MUNI.EUROCOMB23-108 SP - 784 EP - 789 ER - TY - CHAP A1 - Zimmer, Max A1 - Spiegel, Christoph A1 - Pokutta, Sebastian ED - Fackeldey, K. T1 - Compression-aware training of neural networks using Frank-Wolfe T2 - Mathematical Optimization for Machine Learning: Proceedings of the MATH+ Thematic Einstein Semester 2023 Y1 - 2025 U6 - https://doi.org/10.1515/9783111376776-010 SP - 137 EP - 168 PB - De Gruyter ER - TY - JOUR A1 - Pokutta, Sebastian A1 - Spiegel, Christoph A1 - Zimmer, Max T1 - Deep Neural Network Training with Frank-Wolfe N2 - This paper studies the empirical efficacy and benefits of using projection-free first-order methods in the form of Conditional Gradients, a.k.a. Frank-Wolfe methods, for training Neural Networks with constrained parameters. We draw comparisons both to current state-of-the-art stochastic Gradient Descent methods as well as across different variants of stochastic Conditional Gradients. In particular, we show the general feasibility of training Neural Networks whose parameters are constrained by a convex feasible region using Frank-Wolfe algorithms and compare different stochastic variants. We then show that, by choosing an appropriate region, one can achieve performance exceeding that of unconstrained stochastic Gradient Descent and matching state-of-the-art results relying on L2-regularization. Lastly, we also demonstrate that, besides impacting performance, the particular choice of constraints can have a drastic impact on the learned representations. Y1 - 2020 ER -