Mojmír Mutný

• PhD Student
• mojmir.mutny@inf.ethz.ch
• External Website
• OAT Y18
• +41 44 632 74 06
• My research focuses on optimization methods for machine learning, and machine learning methods used as optimization tools. I addition, I am broadly interested in theory of learning, experimental design, active learning and numerical linear algebra. My work tries to deliver practical algorithms with certifiable guarantees.
  Before joining the group, I have obtained a masters degree in Computational Science at ETH Zurich and a bachelors degree in Mathematical Physics at University of Edinburgh. I interned at Disney Research and SwissQuant.

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Publications

2024

Submodular Reinforcement Learning M. Prajapat, M. Mutný, M. N. Zeilinger, A. Krause In Proc. International Conference on Learning Representations (ICLR), 2024 Spotlight presentation [bibtex] [abstract] [pdf]

Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning T. Vornholt, M. Mutný, G. W. Schmidt, R. T. Christian Schellhaas, S. Panke, T. R. Ward, A. Krause, M. Jeschek In ACS Central Science, volume 10, 2024 [bibtex] [abstract] [doi]

2022

Experimental Design of Linear Functionals in Reproducing Kernel Hilbert Spaces M. Mutný, A. Krause In Proc. Neural Information Processing Systems (NeurIPS), 2022 Oral presentation [bibtex] [abstract] [pdf]

Active Exploration via Experiment Design in Markov Chains M. Mutný, T. Janik, A. Krause arXiv, 2022 [bibtex] [abstract] [pdf] [doi]

Sensing Cox Processes via Posterior Sampling and Positive Bases M. Mutný, A. Krause In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 [bibtex] [abstract] [pdf]

Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes E. Nava, M. Mutný, A. Krause In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 [bibtex] [abstract] [pdf]

2021

No-regret Algorithms for Capturing Events in Poisson Point Processes M. Mutný, A. Krause In Proc. International Conference on Machine Learning (ICML), 2021 [bibtex] [abstract] [pdf]

Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory L. Treven, S. Curi, M. Mutný, A. Krause In Proc. Learning for Dynamics and Control (L4DC), 2021 [bibtex] [abstract] [pdf]

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback M. Jourdan, M. Mutný, J. Kirschner, A. Krause In Proc. International Conference on Algorithmic Learning Theory (ALT), 2021 [bibtex] [abstract] [pdf]

2020

Coresets via Bilevel Optimization for Continual Learning and Streaming Z. Borsos, M. Mutný, A. Krause In Proc. Neural Information Processing Systems (NeurIPS), 2020 [bibtex] [abstract] [pdf] [code]

Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling M. Mutný, M. Derezisnki, A. Krause In Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 [bibtex] [abstract] [pdf]

Experimental Design for Optimization of Orthogonal Projection Pursuit Models M. Mutný, J. Kirschner, A. Krause In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020 [bibtex] [abstract] [pdf]

2019

Bayesian Optimization for Fast and Safe Parameter Tuning of SwissFEL J. Kirschner, M. Nonnenmacher, M. Mutný, N. Hiller, A. Adelmann, R. Ischebeck, A. Krause In Proc. International Free-Electron Laser Conference (FEL2019), 2019 [bibtex] [abstract] [pdf]

Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces J. Kirschner, M. Mutný, N. Hiller, R. Ischebeck, A. Krause In Proc. International Conference for Machine Learning (ICML), 2019 [bibtex] [abstract] [pdf]

2018

Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features M. Mutný, A. Krause In Neural and Information Processing Systems (NeurIPS), 2018 Spotlight presentation [bibtex] [abstract] [pdf]

Parallel Stochastic Newton Method M. Mutný, P. Richtárik In Journal of Computational Mathematics, volume 36, 2018 [bibtex] [abstract] [pdf]