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Michael Muehlebach
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2020 – today
- 2024
- [j10]Florian Dörfler
, Zhiyu He
Toward a Systems Theory of Algorithms. IEEE Control. Syst. Lett. 8: 1198-1210 (2024) - [j9]Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach:
Deep Backtracking Counterfactuals for Causally Compliant Explanations. Trans. Mach. Learn. Res. 2024 (2024) - [c22]Anna M. Wundram, Paul Fischer, Michael Mühlebach, Lisa M. Koch, Christian F. Baumgartner:
Conformal Performance Range Prediction for Segmentation Output Quality Control. UNSURE@MICCAI 2024: 81-91 - [c21]Paul Fischer, Hannah Willms, Moritz Schneider, Daniela Thorwarth, Michael Muehlebach, Christian F. Baumgartner:
Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy. MICCAI (10) 2024: 696-706 - [i31]Florian Dörfler, Zhiyu He, Giuseppe Belgioioso, Saverio Bolognani, John Lygeros, Michael Muehlebach:
Towards a Systems Theory of Algorithms. CoRR abs/2401.14029 (2024) - [i30]Jasan Zughaibi, Bradley J. Nelson, Michael Muehlebach:
Balancing a 3D Inverted Pendulum using Remote Magnetic Manipulation. CoRR abs/2402.06012 (2024) - [i29]Liang Zhang, Niao He, Michael Muehlebach:
Primal Methods for Variational Inequality Problems with Functional Constraints. CoRR abs/2403.12859 (2024) - [i28]Zhiyu He, Saverio Bolognani, Michael Muehlebach, Florian Dörfler:
Gray-Box Nonlinear Feedback Optimization. CoRR abs/2404.04355 (2024) - [i27]Hao Ma, Melanie N. Zeilinger, Michael Muehlebach:
Stochastic Online Optimization for Cyber-Physical and Robotic Systems. CoRR abs/2404.05318 (2024) - [i26]Guner Dilsad Er, Sebastian Trimpe, Michael Muehlebach:
Distributed Event-Based Learning via ADMM. CoRR abs/2405.10618 (2024) - [i25]Onno Eberhard, Claire Vernade, Michael Muehlebach:
A Pontryagin Perspective on Reinforcement Learning. CoRR abs/2405.18100 (2024) - [i24]Paul Fischer, Hannah Willms, Moritz Schneider, Daniela Thorwarth, Michael Muehlebach, Christian F. Baumgartner:
Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy. CoRR abs/2407.08432 (2024) - [i23]Anna M. Wundram, Paul Fischer, Michael Muehlebach, Lisa M. Koch, Christian F. Baumgartner:
Conformal Performance Range Prediction for Segmentation Output Quality Control. CoRR abs/2407.13307 (2024) - [i22]Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach:
Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. CoRR abs/2410.01660 (2024) - [i21]Wenshuai Zhao, Yi Zhao, Joni Pajarinen, Michael Muehlebach:
Bi-Level Motion Imitation for Humanoid Robots. CoRR abs/2410.01968 (2024) - 2023
- [j8]Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach:
Reinforcement learning with model-based feedforward inputs for robotic table tennis. Auton. Robots 47(8): 1387-1403 (2023) - [c20]Sholom Schechtman, Daniil Tiapkin
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold. COLT 2023: 1228-1258 - [c19]Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach:
Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. IROS 2023: 567-573 - [c18]Jan Achterhold
Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts. L4DC 2023: 878-890 - [c17]Tong Guanchun, Michael Muehlebach:
A Dynamical Systems Perspective on Discrete Optimization. L4DC 2023: 1373-1386 - [c16]Pavel Kolev, Georg Martius, Michael Muehlebach:
Online Learning under Adversarial Nonlinear Constraints. NeurIPS 2023 - [c15]Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach:
Causal effect estimation from observational and interventional data through matrix weighted linear estimators. UAI 2023: 1087-1097 - [i20]Michael Muehlebach, Michael I. Jordan:
Accelerated First-Order Optimization under Nonlinear Constraints. CoRR abs/2302.00316 (2023) - [i19]Michael Muehlebach:
Adaptive Decision-Making with Constraints and Dependent Losses: Performance Guarantees and Applications to Online and Nonlinear Identification. CoRR abs/2304.03321 (2023) - [i18]Jan Achterhold, Philip Tobuschat, Hao Ma, Dieter Büchler, Michael Muehlebach, Joerg Stueckler:
Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts. CoRR abs/2305.15189 (2023) - [i17]Pavel Kolev, Georg Martius, Michael Muehlebach:
Online Learning under Adversarial Nonlinear Constraints. CoRR abs/2306.03655 (2023) - [i16]Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach:
Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators. CoRR abs/2306.06002 (2023) - [i15]Simon Guist, Jan Schneider, Hao Ma, Vincent Berenz, Julian Martus, Felix Grüninger, Michael Mühlebach, Jonathan Fiene, Bernhard Schölkopf, Dieter Büchler:
A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions. CoRR abs/2307.02654 (2023) - [i14]Philip Tobuschat, Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach:
Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. CoRR abs/2308.14562 (2023) - [i13]Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach:
Deep Backtracking Counterfactuals for Causally Compliant Explanations. CoRR abs/2310.07665 (2023) - 2022
- [j7]Michael Muehlebach, Michael I. Jordan:
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems. J. Mach. Learn. Res. 23: 256:1-256:47 (2022) - [c14]Aniket Das, Bernhard Schölkopf, Michael Muehlebach:
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. NeurIPS 2022 - [c13]Hao Ma, Dieter Büchler, Bernhard Schölkopf, Michael Muehlebach:
A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles. Robotics: Science and Systems 2022 - [i12]Aniket Das, Bernhard Schölkopf, Michael Muehlebach:
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. CoRR abs/2206.02953 (2022) - [i11]Daniel Frank, Decky Aspandi-Latif, Michael Muehlebach, Benjamin Unger, Steffen Staab:
Robust Recurrent Neural Network to Identify Ship Motion in Open Water with Performance Guarantees - Technical Report. CoRR abs/2212.05781 (2022) - 2021
- [j6]Michael Muehlebach, Michael I. Jordan:
Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives. J. Mach. Learn. Res. 22: 73:1-73:50 (2021) - [i10]Michael Muehlebach, Michael I. Jordan:
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems. CoRR abs/2107.08225 (2021) - 2020
- [c12]Michael Muehlebach, Michael I. Jordan:
Continuous-time Lower Bounds for Gradient-based Algorithms. ICML 2020: 7088-7096 - [i9]Michael Muehlebach, Michael I. Jordan:
Continuous-time Lower Bounds for Gradient-based Algorithms. CoRR abs/2002.03546 (2020) - [i8]Michael Muehlebach, Michael I. Jordan:
Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives. CoRR abs/2002.12493 (2020)
2010 – 2019
- 2019
- [j5]Michael Muehlebach
A Method for Reducing the Complexity of Model Predictive Control in Robotics Applications. IEEE Robotics Autom. Lett. 4(3): 2516-2523 (2019) - [c11]Michael Muehlebach, Michael I. Jordan:
A Dynamical Systems Perspective on Nesterov Acceleration. ICML 2019: 4656-4662 - [i7]Michael Muehlebach, Raffaello D'Andrea:
A Method for Reducing the Complexity of Model Predictive Control in Robotics Applications. CoRR abs/1903.07648 (2019) - [i6]Michael Muehlebach, Michael I. Jordan:
A Dynamical Systems Perspective on Nesterov Acceleration. CoRR abs/1905.07436 (2019) - [i5]N. Benjamin Erichson, Michael Muehlebach, Michael W. Mahoney:
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction. CoRR abs/1905.10866 (2019) - [i4]Michael Muehlebach:
The Silver Ratio and its Relation to Controllability. CoRR abs/1908.07109 (2019) - 2018
- [j4]Michael Muehlebach
Distributed Event-Based State Estimation for Networked Systems: An LMI Approach. IEEE Trans. Autom. Control. 63(1): 269-276 (2018) - [j3]Michael Muehlebach
Accelerometer-Based Tilt Determination for Rigid Bodies With a Nonaccelerated Pivot Point. IEEE Trans. Control. Syst. Technol. 26(6): 2106-2120 (2018) - [i3]Michael Muehlebach, Raffaello D'Andrea:
On the Approximation of Constrained Linear Quadratic Regulator Problems and their Application to Model Predictive Control - Supplementary Notes. CoRR abs/1803.05510 (2018) - 2017
- [j2]Michael Muehlebach, Raffaello D'Andrea:
Nonlinear Analysis and Control of a Reaction-Wheel-Based 3-D Inverted Pendulum. IEEE Trans. Control. Syst. Technol. 25(1): 235-246 (2017) - [c10]Carmelo Sferrazza, Michael Muehlebach, Raffaello D'Andrea:
Trajectory tracking and iterative learning on an unmanned aerial vehicle using parametrized model predictive control. CDC 2017: 5186-5192 - [c9]Michael Muehlebach, Raffaello D'Andrea:
Basis functions design for the approximation of constrained linear quadratic regulator problems encountered in model predictive control. CDC 2017: 6189-6196 - [c8]Michael Muehlebach, Carmelo Sferrazza, Raffaello D'Andrea:
Implementation of a parametrized infinite-horizon model predictive control scheme with stability guarantees. ICRA 2017: 2723-2730 - [i2]Michael Muehlebach, Sebastian Trimpe:
Distributed Event-Based State Estimation for Networked Systems: An LMI-Approach. CoRR abs/1707.01659 (2017) - 2016
- [c7]Michael Muehlebach, Raffaello D'Andrea:
Parametrized infinite-horizon model predictive control for linear time-invariant systems with input and state constraints. ACC 2016: 2669-2674 - [c6]Michael Muehlebach, Raffaello D'Andrea:
Approximation of continuous-time infinite-horizon optimal control problems arising in model predictive control. CDC 2016: 1464-1470 - [c5]Matthias Hofer, Michael Muehlebach, Raffaello D'Andrea:
Application of an approximate model predictive control scheme on an unmanned aerial vehicle. ICRA 2016: 2952-2957 - [i1]Michael Muehlebach, Raffaello D'Andrea:
Approximation of Continuous-Time Infinite-Horizon Optimal Control Problems Arising in Model Predictive Control - Supplementary Notes. CoRR abs/1608.08823 (2016) - 2015
- [c4]Michael Muehlebach, Sebastian Trimpe
LMI-based synthesis for distributed event-based state estimation. ACC 2015: 4060-4067 - [c3]Michael Muehlebach, Sebastian Trimpe
Guaranteed ℋ2 performance in distributed event-based state estimation. EBCCSP 2015: 1-8 - 2014
- [j1]Hannes Maes, Gerd Vandersteen, Michael Muehlebach, Clara M. Ionescu
A Fan-Based, Low-Frequent, Forced Oscillation Technique Apparatus. IEEE Trans. Instrum. Meas. 63(3): 603-611 (2014) - 2013
- [c2]Michael Muehlebach, Gajamohan Mohanarajah, Raffaello D'Andrea:
Nonlinear analysis and control of a reaction wheel-based 3D inverted pendulum. CDC 2013: 1283-1288 - [c1]Mohanarajah Gajamohan, Michael Muehlebach, Tobias Widmer, Raffaello D'Andrea:
The Cubli: A reaction wheel based 3D inverted pendulum. ECC 2013: 268-274
Coauthor Index
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last updated on 2024-11-11 21:27 CET by the dblp team
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