Johannes Kirschner
Cited by
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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
Information directed sampling and bandits with heteroscedastic noise
J Kirschner, A Krause
Conference On Learning Theory, 358-384, 2018
Information-Directed Exploration for Deep Reinforcement Learning
N Nikolov, J Kirschner, F Berkenkamp, A Krause
arXiv preprint arXiv:1812.07544, 2018
Distributionally robust bayesian optimization
J Kirschner, I Bogunovic, S Jegelka, A Krause
International Conference on Artificial Intelligence and Statistics, 2174-2184, 2020
Information directed sampling for linear partial monitoring
J Kirschner, T Lattimore, A Krause
Conference on Learning Theory, 2328-2369, 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
Stochastic bandits with context distributions
J Kirschner, A Krause
Advances in Neural Information Processing Systems, 14113-14122, 2019
Asymptotically Optimal Information-Directed Sampling
J Kirschner, T Lattimore, C Vernade, C Szepesvári
arXiv preprint arXiv:2011.05944, 2020
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback
M Jourdan, M Mutný, J Kirschner, A Krause
Algorithmic Learning Theory, 805-849, 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
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