Christoph Dann

According to our database1, Christoph Dann authored at least 42 papers between 2012 and 2024.

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Bibliography

2024
A Minimaximalist Approach to Reinforcement Learning from Human Feedback.
CoRR, 2024

2023
Data-Driven Regret Balancing for Online Model Selection in Bandits.
CoRR, 2023

Best of Both Worlds Policy Optimization.
Proceedings of the International Conference on Machine Learning, 2023

Reinforcement Learning Can Be More Efficient with Multiple Rewards.
Proceedings of the International Conference on Machine Learning, 2023

Learning in POMDPs is Sample-Efficient with Hindsight Observability.
Proceedings of the International Conference on Machine Learning, 2023

A Blackbox Approach to Best of Both Worlds in Bandits and Beyond.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

A Unified Algorithm for Stochastic Path Problems.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Pseudonorm Approachability and Applications to Regret Minimization.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Multiple-policy High-confidence Policy Evaluation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Best of Both Worlds Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation.
Proceedings of the International Conference on Machine Learning, 2022

Same Cause; Different Effects in the Brain.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

A Model Selection Approach for Corruption Robust Reinforcement Learning.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Leveraging Initial Hints for Free in Stochastic Linear Bandits.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021
Neural Active Learning with Performance Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Balancing for Model Selection in Bandits and RL.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Strategic Exploration in Reinforcement Learning - New Algorithms and Learning Guarantees.
PhD thesis, 2020

Regret Bound Balancing and Elimination for Model Selection in Bandits and RL.
CoRR, 2020

Reinforcement Learning with Feedback Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Policy Certificates: Towards Accountable Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
On Polynomial Time PAC Reinforcement Learning with Rich Observations.
CoRR, 2018

On Oracle-Efficient PAC RL with Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Decoupling Gradient-Like Learning Rules from Representations.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Automated matching of pipeline corrosion features from in-line inspection data.
Reliab. Eng. Syst. Saf., 2017

Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

Decoupling Learning Rules from Representations.
CoRR, 2017

UBEV - A More Practical Algorithm for Episodic RL with Near-Optimal PAC and Regret Guarantees.
CoRR, 2017

Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sample Efficient Policy Search for Optimal Stopping Domains.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Memory Lens: How Much Memory Does an Agent Use?
CoRR, 2016

Energetic Natural Gradient Descent.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
RLPy: a value-function-based reinforcement learning framework for education and research.
J. Mach. Learn. Res., 2015

Thoughts on Massively Scalable Gaussian Processes.
CoRR, 2015

The Human Kernel.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Policy Evaluation with Temporal Differences: A Survey and Comparison (Extended Abstract).
Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, 2015

2014
Policy evaluation with temporal differences: a survey and comparison.
J. Mach. Learn. Res., 2014

2012
Pottics - The Potts Topic Model for Semantic Image Segmentation.
Proceedings of the Pattern Recognition, 2012


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