Publications

DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation


Research Groups

Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group


Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

Career

Award


Empirical Inference Learning and Dynamical Systems Conference Paper Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization Das, A., Schölkopf, B., Muehlebach, M. Advances in Neural Information Processing Systems 35, :6749-6762, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), 36th Conference on Neural Information Processing Systems (NeurIPS 2022) , December 2022 (Published) arXiv URL BibTeX

Empirical Inference Learning and Dynamical Systems Conference Paper A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles Ma, H., Büchler, D., Schölkopf, B., Muehlebach, M. Proceedings of Robotics: Science and Systems XVIII (R:SS 2022), 18, (Editors: Kris Hauser, Dylan Shell, and Shoudong Huang), Robotics: Science and Systems XVIII, June 2022 (Published) PDF DOI URL BibTeX

Learning and Dynamical Systems Conference Paper First-order Constrained Optimization: Non-smooth Dynamical System Viewpoint Schechtman, S., Tiapkin, D., Moulines, E., Muehlebach, M. IFAC Workshop on Control Applications of Optimization, 2022 (Published) URL BibTeX

Learning and Dynamical Systems Article On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems Muehlebach, M., Jordan, M. I. Journal of Machine Learning Research, 23, 2022 (Published) URL BibTeX