Johannes Kirschner

According to our database1, Johannes Kirschner authored at least 18 papers between 2018 and 2023.

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Bibliography

2023
Linear Partial Monitoring for Sequential Decision Making: Algorithms, Regret Bounds and Applications.
J. Mach. Learn. Res., 2023

Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off.
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.
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.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization.
CoRR, 2022

2021
Information-Directed Sampling - Frequentist Analysis and Applications.
PhD thesis, 2021

Bias-Robust Bayesian Optimization via Dueling Bandit.
CoRR, 2021

Bias-Robust Bayesian Optimization via Dueling Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021

Asymptotically Optimal Information-Directed Sampling.
Proceedings of the Conference on Learning Theory, 2021

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback.
Proceedings of the Algorithmic Learning Theory, 2021

2020
Information Directed Sampling for Linear Partial Monitoring.
Proceedings of the Conference on Learning Theory, 2020

Distributionally Robust Bayesian Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Experimental Design for Optimization of Orthogonal Projection Pursuit Models.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Stochastic Bandits with Context Distributions.
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.
Proceedings of the 36th International Conference on Machine Learning, 2019

Information-Directed Exploration for Deep Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Information Directed Sampling and Bandits with Heteroscedastic Noise.
Proceedings of the Conference On Learning Theory, 2018


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