Muehlebach, Michael

27 publications

MLJ 2026 Stochastic Online Optimization for Cyber-Physical and Robotic Systems Hao Ma, Melanie Nicole Zeilinger, Michael Muehlebach

L4DC 2025 A Pontryagin Perspective on Reinforcement Learning Onno Eberhard, Claire Vernade, Michael Muehlebach

ICLR 2025 Adversarial Training for Defense Against Label Poisoning Attacks Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach

ICLR 2025 Conformal Generative Modeling with Improved Sample Efficiency Through Sequential Greedy Filtering Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach

CoRL 2025 Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racing Hao Ma, Sabrina Bodmer, Andrea Carron, Melanie Zeilinger, Michael Muehlebach

L4DC 2025 Controlling Participation in Federated Learning with Feedback Michael Cummins, Guner Dilsad Er, Michael Muehlebach

ICML 2025 Distributed Event-Based Learning via ADMM Guner Dilsad Er, Sebastian Trimpe, Michael Muehlebach

NeurIPS 2025 Fast Non-Log-Concave Sampling Under Nonconvex Equality and Inequality Constraints with Landing Kijung Jeon, Michael Muehlebach, Molei Tao

ICML 2025 Partially Observable Reinforcement Learning with Memory Traces Onno Eberhard, Michael Muehlebach, Claire Vernade

NeurIPS 2025 Quantization-Free Autoregressive Action Transformer Ziyad Sheebaelhamd, Michael Tschannen, Michael Muehlebach, Claire Vernade

NeurIPS 2025 Zeroth-Order Optimization Finds Flat Minima Liang Zhang, Bingcong Li, Kiran Koshy Thekumparampil, Sewoong Oh, Michael Muehlebach, Niao He

ICMLW 2024 A Pontryagin Perspective on Reinforcement Learning Onno Eberhard, Claire Vernade, Michael Muehlebach

CoRL 2024 Bi-Level Motion Imitation for Humanoid Robots Wenshuai Zhao, Yi Zhao, Joni Pajarinen, Michael Muehlebach

TMLR 2024 Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach

ICMLW 2024 Event-Based Federated Q-Learning Guner Dilsad Er, Michael Muehlebach

ICMLW 2024 Online Optimization of Closed-Loop Control Systems Hao Ma, Melanie Zeilinger, Michael Muehlebach

ICMLW 2024 Online Performance Optimization of Nonlinear Systems: A Gray-Box Approach Zhiyu He, Michael Muehlebach, Saverio Bolognani, Florian Dorfler

L4DC 2023 A Dynamical Systems Perspective on Discrete Optimization Tong Guanchun, Michael Muehlebach

L4DC 2023 Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts Jan Achterhold, Philip Tobuschat, Hao Ma, Dieter Büchler, Michael Muehlebach, Joerg Stueckler

UAI 2023 Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators Klaus-Rudolf Kladny, Julius Kügelgen, Bernhard Schölkopf, Michael Muehlebach

NeurIPS 2023 Online Learning Under Adversarial Nonlinear Constraints Pavel Kolev, Georg Martius, Michael Muehlebach

COLT 2023 Orthogonal Directions Constrained Gradient Method: From Non-Linear Equality Constraints to Stiefel Manifold Sholom Schechtman, Daniil Tiapkin, Michael Muehlebach, Éric Moulines

JMLR 2022 On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems Michael Muehlebach, Michael I. Jordan

NeurIPS 2022 Sampling Without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization Aniket Das, Bernhard Schölkopf, Michael Muehlebach

JMLR 2021 Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives Michael Muehlebach, Michael I. Jordan

ICML 2020 Continuous-Time Lower Bounds for Gradient-Based Algorithms Michael Muehlebach, Michael Jordan

ICML 2019 A Dynamical Systems Perspective on Nesterov Acceleration Michael Muehlebach, Michael Jordan