← Authors

Sebastian Pokutta

47 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (9) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (7) πŸ† Grand Slam πŸ”¬ Deep Specialist (18) πŸ† Keyword Champion (3) πŸ”₯ Unstoppable (7) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (125) ⚑ Prolific Year (5) πŸ’Ž Century Club (47)

Conferences

ICML (18) AISTATS (10) NIPS (8) ICLR (5) JMLR (3) COLT (2) AAAI (1)

Top co-authors

Max Zimmer (8) Christophe Roux (5) David Martínez-Rubio (4) Christoph Spiegel (4) Thomas Kerdreux (4) Elias Samuel Wirth (3) Alejandro Carderera (3) Mathieu Besançon (3) Aurko Roy (3) GÑbor Braun (3)

Keywords

frank-wolfe algorithm (12) convex optimization (11) conditional gradient (8) online learning (5) projection-free optimization (4) linear convergence (3) separation oracle (3) kernel herding (2) convergence rate (2) accelerated convergence (2) regret bound (2) approximation algorithm (2) first-order method (2) integer linear programming (2) gradient descent (2) matching pursuit (2) sparse representation (2) hierarchical clustering (2) constrained optimization (2) integer programming (2)

Papers

Neural Discovery in Mathematics: Do Machines Dream of Colored Planes? ICML 2025
Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation ICML 2025
On the Byzantine-Resilience of Distillation-Based Federated Learning ICLR 2025
GSE: Group-wise Sparse and Explainable Adversarial Attacks ICLR 2025
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals ICML 2025
S-CFE: Simple Counterfactual Explanations AISTATS 2025
The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control AISTATS 2025
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties AISTATS 2025
Secant Line Search for Frank-Wolfe Algorithms ICML 2025
Implicit Riemannian Optimism with Applications to Min-Max Problems ICML 2025
Interpretability Guarantees with Merlin-Arthur Classifiers AISTATS 2024
Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point ICML 2024
Estimating Canopy Height at Scale ICML 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
Approximate Vanishing Ideal Computations at Scale ICLR 2023
Learning Cuts via Enumeration Oracles NIPS 2023
Fully Computer-Assisted Proofs in Extremal Combinatorics AAAI 2023
Acceleration of Frank-Wolfe Algorithms with Open-Loop Step-Sizes AISTATS 2023
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties COLT 2023
How I Learned to Stop Worrying and Love Retraining ICLR 2023
Training Characteristic Functions with Reinforcement Learning: XAI-methods play Connect Four ICML 2022
Fast Algorithms for Packing Proportional Fairness and its Dual NIPS 2022
Conditional Gradients for the Approximately Vanishing Ideal AISTATS 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
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions NIPS 2021
Projection-Free Optimization on Uniformly Convex Sets AISTATS 2021
Parameter-free Locally Accelerated Conditional Gradients ICML 2021
Linear Bandits on Uniformly Convex Sets JMLR 2021
Learning to Schedule Heuristics in Branch and Bound NIPS 2021
IPBoost – Non-Convex Boosting via Integer Programming ICML 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 NIPS 2020
Locally Accelerated Conditional Gradients AISTATS 2020
Boosting Frank-Wolfe by Chasing Gradients ICML 2020
Structured Robust Submodular Maximization: Offline and Online Algorithms AISTATS 2019
Blended Matching Pursuit NIPS 2019
Restarting Frank-Wolfe AISTATS 2019
Lazifying Conditional Gradient Algorithms JMLR 2019
Blended Conditonal Gradients ICML 2019
Emulating the Expert: Inverse Optimization through Online Learning ICML 2017
Lazifying Conditional Gradient Algorithms ICML 2017
Conditional Accelerated Lazy Stochastic Gradient Descent ICML 2017
Reinforcement Learning under Model Mismatch NIPS 2017
Hierarchical Clustering via Spreading Metrics JMLR 2017
Hierarchical Clustering via Spreading Metrics NIPS 2016