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ORCIDMojmír Mutný
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Books and Theses
- 2024
[b1]Mojmír Mutný:
Modern Adaptive Experiment Design: Machine Learning Perspective. ETH Zurich, Zürich, Switzerland, 2024
Journal Articles
- 2024
- [j1]Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi, Andreas Krause:
Data Summarization via Bilevel Optimization. J. Mach. Learn. Res. 25: 73:1-73:53 (2024)
Conference and Workshop Papers
- 2024
- [c14]Manish Prajapat, Mojmir Mutny, Melanie N. Zeilinger, Andreas Krause:
Submodular Reinforcement Learning. ICLR 2024 - 2023
- [c13]Mojmir Mutny, Tadeusz Janik, Andreas Krause:
Active Exploration via Experiment Design in Markov Chains. AISTATS 2023: 7349-7374 - [c12]Nicolas Emmenegger, Mojmir Mutny, Andreas Krause:
Likelihood Ratio Confidence Sets for Sequential Decision Making. NeurIPS 2023 - 2022
- [c11]Mojmir Mutny, Andreas Krause:
Sensing Cox Processes via Posterior Sampling and Positive Bases. AISTATS 2022: 6968-6989 - [c10]Elvis Nava, Mojmir Mutny, Andreas Krause:
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. AISTATS 2022: 7031-7054 - [c9]Mojmir Mutny, Andreas Krause:
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. NeurIPS 2022 - 2021
- [c8]Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause:
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. ALT 2021: 805-849 - [c7]Mojmir Mutny, Andreas Krause:
No-regret Algorithms for Capturing Events in Poisson Point Processes. ICML 2021: 7894-7904 - [c6]Lenart Treven, Sebastian Curi, Mojmír Mutný, Andreas Krause:
Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. L4DC 2021: 664-676 - 2020
- [c5]Mojmir Mutny, Johannes Kirschner, Andreas Krause:
Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI 2020: 10235-10242 - [c4]Mojmir Mutny, Michal Derezinski, Andreas Krause:
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling. AISTATS 2020: 3110-3120 - [c3]Zalán Borsos, Mojmir Mutny, Andreas Krause:
Coresets via Bilevel Optimization for Continual Learning and Streaming. NeurIPS 2020 - 2019
- [c2]Johannes Kirschner, Mojmir Mutny, Nicole Hiller, Rasmus Ischebeck, Andreas Krause:
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. ICML 2019: 3429-3438 - 2018
- [c1]Mojmir Mutny, Andreas Krause:
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features. NeurIPS 2018: 9019-9030
Informal and Other Publications
- 2024
- [i17]Jose Pablo Folch, Calvin Tsay, Robert M. Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný:
Transition Constrained Bayesian Optimization via Markov Decision Processes. CoRR abs/2402.08406 (2024) - [i16]Melis Ilayda Bal, Pier Giuseppe Sessa, Mojmir Mutny, Andreas Krause:
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design. CoRR abs/2409.18582 (2024) - 2023
- [i15]Manish Prajapat, Mojmír Mutný, Melanie N. Zeilinger, Andreas Krause:
Submodular Reinforcement Learning. CoRR abs/2307.13372 (2023) - [i14]Nicolas Emmenegger, Mojmír Mutný
, Andreas Krause:
Likelihood Ratio Confidence Sets for Sequential Decision Making. CoRR abs/2311.04402 (2023) - 2022
- [i13]Johannes Kirschner, Mojmír Mutný, Andreas Krause, Jaime Coello de Portugal, Nicole Hiller, Jochem Snuverink:
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization. CoRR abs/2203.13968 (2022) - [i12]Mojmír Mutný, Andreas Krause:
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. CoRR abs/2205.13627 (2022) - [i11]Mojmír Mutný, Tadeusz Janik, Andreas Krause:
Active Exploration via Experiment Design in Markov Chains. CoRR abs/2206.14332 (2022) - 2021
- [i10]Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause:
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. CoRR abs/2101.08534 (2021) - [i9]Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi, Andreas Krause:
Data Summarization via Bilevel Optimization. CoRR abs/2109.12534 (2021) - [i8]Mojmír Mutný, Andreas Krause:
Sensing Cox Processes via Posterior Sampling and Positive Bases. CoRR abs/2110.11181 (2021) - [i7]Elvis Nava, Mojmír Mutný, Andreas Krause:
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. CoRR abs/2110.11665 (2021) - 2020
- [i6]Zalán Borsos, Mojmír Mutný, Andreas Krause:
Coresets via Bilevel Optimization for Continual Learning and Streaming. CoRR abs/2006.03875 (2020) - [i5]Lenart Treven, Sebastian Curi, Mojmir Mutny, Andreas Krause:
Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. CoRR abs/2006.11022 (2020) - 2019
- [i4]Johannes Kirschner, Mojmír Mutný, Nicole Hiller, Rasmus Ischebeck, Andreas Krause:
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. CoRR abs/1902.03229 (2019) - [i3]Mojmír Mutný, Michal Derezinski, Andreas Krause:
Convergence Analysis of the Randomized Newton Method with Determinantal Sampling. CoRR abs/1910.11561 (2019) - 2016
- [i2]Mojmir Mutny:
Stochastic Second-Order Optimization via von Neumann Series. CoRR abs/1612.04694 (2016) - 2015
- [i1]Mojmir Mutny, Rahul Nair, Jens-Malte Gottfried:
Learning the Correction for Multi-Path Deviations in Time-of-Flight Cameras. CoRR abs/1512.04077 (2015)
Coauthor Index
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