Intelligent Systems



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Conformal Performance Range Prediction for Segmentation Output Quality Control

Wundram, A., Fischer, P., Muehlebach, M., Koch, L., Baumgartner, C.

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024 (conference) Submitted

[BibTex]

[BibTex]


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Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy

Fischer, P., Willms, H., Muehlebach, M., Thorwarth, D., Schneider, M., Baumgartner, C.

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024 (conference)

[BibTex]

[BibTex]


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Online learning under adversarial nonlinear constraints

Kolev, P., Martius, G., Muehlebach, M.

In Advances in Neural Information Processing Systems 36, 2024 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]

2023


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Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators

Kladny, K., von Kügelgen, J., Schölkopf, B., Muehlebach, M.

Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI), 216, pages: 1087-1097, Proceedings of Machine Learning Research, (Editors: Evans, Robin J. and Shpitser, Ilya), PMLR, August 2023 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts

Achterhold, J., Tobuschat, P., Ma, H., Büchler, D., Muehlebach, M., Stueckler, J.

In Proceedings of the 5th Annual Learning for Dynamics and Control Conference (L4DC), 211, pages: 878-890, Proceedings of Machine Learning Research, (Editors: Nikolai Matni, Manfred Morari and George J. Pappa), PMLR, June 2023 (inproceedings)

preprint code link (url) [BibTex]

preprint code link (url) [BibTex]


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A Dynamical Systems Perspective on Discrete Optimization

Tong, G., Muehlebach, M.

Conference on Learning for Dynamics and Control, 2023 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Data-Efficient Online Learning of Ball Placement in Robot Table Tennis

Tobuschat, P., Ma, H., Büchler, D., Schölkopf, B., Muehlebach, M.

EEE/RSJ International Conference on Intelligent Robots and Systems, 2023 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Orthogonal Directions Constrained Gradient Method: from Non-Linear Equality Constraints to Stiefel Manifold

Schechtman, S., Tiapkin, D., Muehlebach, M., Moulines, E.

Conference on Learning Theory, 2023 (conference)

link (url) [BibTex]

link (url) [BibTex]

2022


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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 (NeurIPS 2022), pages: 6749-6762, (Editors: S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh), Curran Associates, Inc., 36th Conference on Neural Information Processing Systems (NeurIPS 2022) , December 2022 (conference)

arXiv link (url) [BibTex]

2022

arXiv link (url) [BibTex]


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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 (conference)

PDF link (url) DOI [BibTex]

PDF link (url) DOI [BibTex]


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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 (conference)

link (url) [BibTex]

link (url) [BibTex]

2021


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Optimization with Adaptive Step Size Selection from a Dynamical Systems Perspective

Wadia, N. S., Jordan, M. I., Muehlebach, M.

OPT2021 Workshop, Conference on Neural Information Processing Systems, Thirty-fifth Conference on Neural Information Processing Systems, 2021 (conference)

link (url) [BibTex]

2021

link (url) [BibTex]

2015


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LMI-Based Synthesis for Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceedings of the American Control Conference, July 2015 (inproceedings)

Abstract
This paper presents an LMI-based synthesis procedure for distributed event-based state estimation. Multiple agents observe and control a dynamic process by sporadically exchanging data over a broadcast network according to an event-based protocol. In previous work [1], the synthesis of event-based state estimators is based on a centralized design. In that case three different types of communication are required: event-based communication of measurements, periodic reset of all estimates to their joint average, and communication of inputs. The proposed synthesis problem eliminates the communication of inputs as well as the periodic resets (under favorable circumstances) by accounting explicitly for the distributed structure of the control system.

PDF DOI Project Page [BibTex]

2015

PDF DOI Project Page [BibTex]


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Guaranteed H2 Performance in Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]