Johannes Kirschner

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 28

Top Topics

High Dimensions

Monte Carlo Sampling

Orthogonal Projection

Reinforcement Learning

Top Venues

Publications

Johannes Kirschner, Seyed Alireza Bakhtiari, Kushagra Chandak, Volodymyr Tkachuk, Csaba Szepesvári
Regret Minimization via Saddle Point Optimization. CoRR (2024)
Zichen Vincent Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub, Masood Dehghan, Dale Schuurmans
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off. NeurIPS (2023)
Johannes Kirschner, Tor Lattimore, Andreas Krause
Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications. CoRR (2023)
Volodymyr Tkachuk, Seyed Alireza Bakhtiari, Johannes Kirschner, Matej Jusup, Ilija Bogunovic, Csaba Szepesvári
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning. AISTATS (2023)
Volodymyr Tkachuk, Seyed Alireza Bakhtiari, Johannes Kirschner, Matej Jusup, Ilija Bogunovic, Csaba Szepesvári
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning. CoRR (2023)
Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic
Near-optimal Policy Identification in Active Reinforcement Learning. ICLR (2023)
Johannes Kirschner, Seyed Alireza Bakhtiari, Kushagra Chandak, Volodymyr Tkachuk, Csaba Szepesvári
Regret Minimization via Saddle Point Optimization. NeurIPS (2023)
Zichen Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub, Masood Dehghan, Dale Schuurmans
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off. CoRR (2022)
Johannes Kirschner, Mojmír Mutný, Andreas Krause, Jaime Coello de Portugal, Nicole Hiller, Jochem Snuverink
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization. CoRR (2022)
Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic
Near-optimal Policy Identification in Active Reinforcement Learning. CoRR (2022)
Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. ALT (2021)
Johannes Kirschner, Andreas Krause
Bias-Robust Bayesian Optimization via Dueling Bandit. CoRR (2021)
Johannes Kirschner, Andreas Krause
Bias-Robust Bayesian Optimization via Dueling Bandits. ICML (2021)
Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. CoRR (2021)
Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvári
Asymptotically Optimal Information-Directed Sampling. COLT (2021)
Johannes Kirschner, Tor Lattimore, Claire Vernade, Csaba Szepesvári
Asymptotically Optimal Information-Directed Sampling. CoRR (2020)
Johannes Kirschner, Tor Lattimore, Andreas Krause
Information Directed Sampling for Linear Partial Monitoring. COLT (2020)
Johannes Kirschner, Tor Lattimore, Andreas Krause
Information Directed Sampling for Linear Partial Monitoring. CoRR (2020)
Mojmir Mutny, Johannes Kirschner, Andreas Krause
Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI (2020)
Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause
Distributionally Robust Bayesian Optimization. CoRR (2020)
Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause
Distributionally Robust Bayesian Optimization. AISTATS (2020)
Johannes Kirschner, Andreas Krause
Stochastic Bandits with Context Distributions. NeurIPS (2019)
Johannes Kirschner, Mojmir Mutny, Nicole Hiller, Rasmus Ischebeck, Andreas Krause
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. ICML (2019)
Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause
Information-Directed Exploration for Deep Reinforcement Learning. ICLR (Poster) (2019)
Johannes Kirschner, Andreas Krause
Stochastic Bandits with Context Distributions. CoRR (2019)
Johannes Kirschner, Mojmír Mutný, Nicole Hiller, Rasmus Ischebeck, Andreas Krause
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. CoRR (2019)
Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause
Information-Directed Exploration for Deep Reinforcement Learning. CoRR (2018)
Johannes Kirschner, Andreas Krause
Information Directed Sampling and Bandits with Heteroscedastic Noise. COLT (2018)