Johannes Kirschner

According to our database, Johannes Kirschner authored at least 18 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Linear Partial Monitoring for Sequential Decision Making: Algorithms, Regret Bounds and Applications.

Johannes Kirschner, Tor Lattimore, Andreas Krause

J. Mach. Learn. Res., 2023

Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off.

Zichen Vincent Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub, Masood Dehghan, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Regret Minimization via Saddle Point Optimization.

Johannes Kirschner, Seyed Alireza Bakhtiari, Kushagra Chandak, Volodymyr Tkachuk, Csaba Szepesvári

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Near-optimal Policy Identification in Active Reinforcement Learning.

Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning.

Volodymyr Tkachuk, Seyed Alireza Bakhtiari, Johannes Kirschner, Matej Jusup, Ilija Bogunovic, Csaba Szepesvári

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization.

Johannes Kirschner, Mojmír Mutný, Andreas Krause, Jaime Coello de Portugal, Nicole Hiller, Jochem Snuverink

CoRR, 2022

2021

Information-Directed Sampling - Frequentist Analysis and Applications.

Johannes Kirschner

PhD thesis, 2021

Bias-Robust Bayesian Optimization via Dueling Bandit.

Johannes Kirschner, Andreas Krause

CoRR, 2021

Bias-Robust Bayesian Optimization via Dueling Bandits.

Johannes Kirschner, Andreas Krause

Proceedings of the 38th International Conference on Machine Learning, 2021

Asymptotically Optimal Information-Directed Sampling.

Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvári

Proceedings of the Conference on Learning Theory, 2021

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback.

Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause

Proceedings of the Algorithmic Learning Theory, 2021

2020

Information Directed Sampling for Linear Partial Monitoring.

Johannes Kirschner, Tor Lattimore, Andreas Krause

Proceedings of the Conference on Learning Theory, 2020

Distributionally Robust Bayesian Optimization.

Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Experimental Design for Optimization of Orthogonal Projection Pursuit Models.

Mojmir Mutny, Johannes Kirschner, Andreas Krause

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Stochastic Bandits with Context Distributions.

Johannes Kirschner, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces.

Johannes Kirschner, Mojmir Mutny, Nicole Hiller, Rasmus Ischebeck, Andreas Krause

Proceedings of the 36th International Conference on Machine Learning, 2019

Information-Directed Exploration for Deep Reinforcement Learning.

Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Information Directed Sampling and Bandits with Heteroscedastic Noise.

Johannes Kirschner, Andreas Krause

Proceedings of the Conference On Learning Theory, 2018