| Adaptive and safe Bayesian optimization in high dimensions via one-dimensional subspaces J Kirschner, M Mutny, N Hiller, R Ischebeck, A Krause International Conference on Machine Learning, 3429-3438, 2019 | 118 | 2019 |
| Information directed sampling and bandits with heteroscedastic noise J Kirschner, A Krause Conference On Learning Theory, 358-384, 2018 | 90 | 2018 |
| Information-Directed Exploration for Deep Reinforcement Learning N Nikolov, J Kirschner, F Berkenkamp, A Krause arXiv preprint arXiv:1812.07544, 2018 | 80 | 2018 |
| Distributionally robust bayesian optimization J Kirschner, I Bogunovic, S Jegelka, A Krause International Conference on Artificial Intelligence and Statistics, 2174-2184, 2020 | 72 | 2020 |
| Asymptotically optimal information-directed sampling J Kirschner, T Lattimore, C Vernade, C Szepesvári Conference on Learning Theory, 2777-2821, 2021 | 29 | 2021 |
| Information directed sampling for linear partial monitoring J Kirschner, T Lattimore, A Krause Conference on Learning Theory, 2328-2369, 2020 | 28 | 2020 |
| Bayesian Optimisation for Fast and Safe Parameter Tuning of SwissFEL J Kirschner, M Nonnenmacher, M Mutný, A Krause, N Hiller, R Ischebeck, ... FEL2019, Proceedings of the 39th International Free-Electron Laser …, 2019 | 20 | 2019 |
| Stochastic bandits with context distributions J Kirschner, A Krause Advances in Neural Information Processing Systems, 14113-14122, 2019 | 20 | 2019 |
| Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback M Jourdan, M Mutný, J Kirschner, A Krause Algorithmic Learning Theory, 805-849, 2021 | 18 | 2021 |
| Tuning particle accelerators with safety constraints using Bayesian optimization J Kirschner, M Mutný, A Krause, JC de Portugal, N Hiller, J Snuverink Physical Review Accelerators and Beams 25 (6), 062802, 2022 | 15 | 2022 |
| Bias-Robust Bayesian Optimization via Dueling Bandits J Kirschner, A Krause arXiv preprint arXiv:2105.11802, 2021 | 9 | 2021 |
| Information-Directed Sampling-Frequentist Analysis and Applications J Kirschner ETH Zurich, 2021 | 7 | 2021 |
| Experimental Design for Optimization of Orthogonal Projection Pursuit Models M Mutny, J Kirschner, A Krause Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10235 …, 2020 | 6 | 2020 |
| Near-optimal Policy Identification in Active Reinforcement Learning X Li, V Mehta, J Kirschner, I Char, W Neiswanger, J Schneider, A Krause, ... arXiv preprint arXiv:2212.09510, 2022 | 3 | 2022 |
| Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications J Kirschner, T Lattimore, A Krause arXiv preprint arXiv:2302.03683, 2023 | 1 | 2023 |
| Regret Minimization via Saddle Point Optimization J Kirschner, A Bakhtiari, K Chandak, V Tkachuk, C Szepesvari Sixteenth European Workshop on Reinforcement Learning, 2023 | | 2023 |
| Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning V Tkachuk, SA Bakhtiari, J Kirschner, M Jusup, I Bogunovic, C Szepesvári International Conference on Artificial Intelligence and Statistics, 6342-6370, 2023 | | 2023 |
| Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off Z Zhang, J Kirschner, J Zhang, F Zanini, A Ayoub, M Dehghan, ... arXiv preprint arXiv:2212.08949, 2022 | | 2022 |
| Real-time railway (re-) scheduling without human-expert knowledge F Corman, M Jusup, J Kirschner, T Birchler, S Curi, I Bogunovic, A Krause 22nd Swiss Transport Research Conference (STRC 2022), 2022 | | 2022 |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
