Sebastian Pokutta

Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties AISTATS 2025 Approximating Latent Manifolds in Neural Networks via Vanishing Ideals ICML 2025 Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation ICML 2025 GSE: Group-wise Sparse and Explainable Adversarial Attacks ICLR 2025 Implicit Riemannian Optimism with Applications to Min-Max Problems ICML 2025 Neural Discovery in Mathematics: Do Machines Dream of Colored Planes? ICML 2025 On the Byzantine-Resilience of Distillation-Based Federated Learning ICLR 2025 S-CFE: Simple Counterfactual Explanations AISTATS 2025 Secant Line Search for Frank-Wolfe Algorithms ICML 2025 The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control AISTATS 2025 Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point ICML 2024 Estimating Canopy Height at Scale ICML 2024 Interpretability Guarantees with Merlin-Arthur Classifiers AISTATS 2024 Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging ICLR 2024 Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond COLT 2023 Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties COLT 2023 Acceleration of Frank-Wolfe Algorithms with Open-Loop Step-Sizes AISTATS 2023 Approximate Vanishing Ideal Computations at Scale ICLR 2023 Fully Computer-Assisted Proofs in Extremal Combinatorics AAAI 2023 How I Learned to Stop Worrying and Love Retraining ICLR 2023 Learning Cuts via Enumeration Oracles NeurIPS 2023 Conditional Gradients for the Approximately Vanishing Ideal AISTATS 2022 Fast Algorithms for Packing Proportional Fairness and its Dual NeurIPS 2022 Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings ICML 2022 Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding ICML 2022 Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four ICML 2022 Learning to Schedule Heuristics in Branch and Bound NeurIPS 2021 Linear Bandits on Uniformly Convex Sets JMLR 2021 Parameter-free Locally Accelerated Conditional Gradients ICML 2021 Projection-Free Optimization on Uniformly Convex Sets AISTATS 2021 Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions NeurIPS 2021 Boosting Frank-Wolfe by Chasing Gradients ICML 2020 IPBoost – Non-Convex Boosting via Integer Programming ICML 2020 Locally Accelerated Conditional Gradients AISTATS 2020 On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness ICML 2020 Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization NeurIPS 2020 Blended Conditonal Gradients ICML 2019 Blended Matching Pursuit NeurIPS 2019 Lazifying Conditional Gradient Algorithms JMLR 2019 Restarting Frank-Wolfe AISTATS 2019 Structured Robust Submodular Maximization: Offline and Online Algorithms AISTATS 2019 Conditional Accelerated Lazy Stochastic Gradient Descent ICML 2017 Emulating the Expert: Inverse Optimization through Online Learning ICML 2017 Hierarchical Clustering via Spreading Metrics JMLR 2017 Lazifying Conditional Gradient Algorithms ICML 2017 Reinforcement Learning under Model Mismatch NeurIPS 2017 Hierarchical Clustering via Spreading Metrics NeurIPS 2016