| 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 | 168 | 2019 |
| Information directed sampling and bandits with heteroscedastic noise J Kirschner, A Krause Conference On Learning Theory, 358-384, 2018 | 123 | 2018 |
| Information-directed exploration for deep reinforcement learning N Nikolov, J Kirschner, F Berkenkamp, A Krause arXiv preprint arXiv:1812.07544, 2018 | 94 | 2018 |
| Distributionally robust Bayesian optimization J Kirschner, I Bogunovic, S Jegelka, A Krause International Conference on Artificial Intelligence and Statistics, 2174-2184, 2020 | 93 | 2020 |
| Information directed sampling for linear partial monitoring J Kirschner, T Lattimore, A Krause Conference on Learning Theory, 2328-2369, 2020 | 55 | 2020 |
| Asymptotically optimal information-directed sampling J Kirschner, T Lattimore, C Vernade, C Szepesvári Conference on Learning Theory, 2777-2821, 2021 | 40 | 2021 |
| Stochastic bandits with context distributions J Kirschner, A Krause Advances in Neural Information Processing Systems, 14113-14122, 2019 | 32 | 2019 |
| Tuning particle accelerators with safety constraints using Bayesian optimization J Kirschner, M Mutný, A Krause, J Coello de Portugal, N Hiller, ... Physical Review Accelerators and Beams 25 (6), 062802, 2022 | 30 | 2022 |
| 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 | 28 | 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 | 27 | 2021 |
| Bias-Robust Bayesian Optimization via Dueling Bandits J Kirschner, A Krause arXiv preprint arXiv:2105.11802, 2021 | 12 | 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 | 10 | 2020 |
| Information-Directed Sampling-Frequentist Analysis and Applications J Kirschner ETH Zurich, 2021 | 8 | 2021 |
| 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 | 7 | 2022 |
| Linear partial monitoring for sequential decision making: Algorithms, regret bounds and applications J Kirschner, T Lattimore, A Krause The Journal of Machine Learning Research 24 (1), 16606-16650, 2023 | 5 | 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 | 3 | 2023 |
| Regret minimization via saddle point optimization J Kirschner, A Bakhtiari, K Chandak, V Tkachuk, C Szepesvári Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| Managing temporal resolution in continuous value estimation: A fundamental trade-off ZV Zhang, J Kirschner, J Zhang, F Zanini, A Ayoub, M Dehghan, ... Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| 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
