Christoph Dann

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 63

Top Topics

Temporal Difference

Reinforcement Learning

Top Venues

Publications

Gokul Swamy, Christoph Dann, Rahul Kidambi, Zhiwei Steven Wu, Alekh Agarwal
A Minimaximalist Approach to Reinforcement Learning from Human Feedback. CoRR (2024)
Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent
Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. CoRR (2024)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan
Rate-Preserving Reductions for Blackwell Approachability. CoRR (2024)
Christoph Dann, Claudio Gentile, Aldo Pacchiano
Data-Driven Online Model Selection With Regret Guarantees. AISTATS (2024)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan
Pseudonorm Approachability and Applications to Regret Minimization. ALT (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond. COLT (2023)
Christoph Dann, Mohammad Ghavamzadeh, Teodor V. Marinov
Multiple-policy High-confidence Policy Evaluation. AISTATS (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
Best of Both Worlds Policy Optimization. CoRR (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Unified Algorithm for Stochastic Path Problems. ALT (2023)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan
Pseudonorm Approachability and Applications to Regret Minimization. CoRR (2023)
Aldo Pacchiano, Christoph Dann, Claudio Gentile
Data-Driven Regret Balancing for Online Model Selection in Bandits. CoRR (2023)
Jonathan N. Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
Learning in POMDPs is Sample-Efficient with Hindsight Observability. CoRR (2023)
Christoph Dann, Yishay Mansour, Mehryar Mohri
Reinforcement Learning Can Be More Efficient with Multiple Rewards. ICML (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond. CoRR (2023)
Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
Learning in POMDPs is Sample-Efficient with Hindsight Observability. ICML (2023)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
Best of Both Worlds Policy Optimization. ICML (2023)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. CoRR (2022)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. ICML (2022)
Aldo Pacchiano, Christoph Dann, Claudio Gentile
Best of Both Worlds Model Selection. NeurIPS (2022)
Aldo Pacchiano, Christoph Dann, Claudio Gentile
Best of Both Worlds Model Selection. CoRR (2022)
Christoph Dann, Chen-Yu Wei, Julian Zimmert
A Unified Algorithm for Stochastic Path Problems. CoRR (2022)
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang
Leveraging Initial Hints for Free in Stochastic Linear Bandits. ALT (2022)
Chen-Yu Wei, Christoph Dann, Julian Zimmert
A Model Selection Approach for Corruption Robust Reinforcement Learning. ALT (2022)
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang
Leveraging Initial Hints for Free in Stochastic Linear Bandits. CoRR (2022)
Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe
Same Cause; Different Effects in the Brain. CLeaR (2022)
Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe
Same Cause; Different Effects in the Brain. CoRR (2022)
Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. CoRR (2022)
Christoph Dann, Teodor V. Marinov, Mehryar Mohri, Julian Zimmert
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning. CoRR (2021)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. CoRR (2021)
Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. NeurIPS (2021)
Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning. NeurIPS (2021)
Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations. NeurIPS (2021)
Chen-Yu Wei, Christoph Dann, Julian Zimmert
A Model Selection Approach for Corruption Robust Reinforcement Learning. CoRR (2021)
Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile
Neural Active Learning with Performance Guarantees. NeurIPS (2021)
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit
Dynamic Balancing for Model Selection in Bandits and RL. ICML (2021)
Pranjal Awasthi, Christoph Dann, Claudio Gentile, Ayush Sekhari, Zhilei Wang
Neural Active Learning with Performance Guarantees. CoRR (2021)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
Reinforcement Learning with Feedback Graphs. CoRR (2020)
Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan
Reinforcement Learning with Feedback Graphs. NeurIPS (2020)
Aldo Pacchiano, Christoph Dann, Claudio Gentile, Peter L. Bartlett
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL. CoRR (2020)
Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. AAAI (2020)
Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
Policy Certificates: Towards Accountable Reinforcement Learning. ICML (2019)
Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. CoRR (2019)
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
On Oracle-Efficient PAC RL with Rich Observations. NeurIPS (2018)
Philip S. Thomas, Christoph Dann, Emma Brunskill
Decoupling Gradient-Like Learning Rules from Representations. ICML (2018)
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
On Polynomial Time PAC Reinforcement Learning with Rich Observations. CoRR (2018)
Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
Policy Certificates: Towards Accountable Reinforcement Learning. CoRR (2018)
Philip S. Thomas, Christoph Dann, Emma Brunskill
Decoupling Learning Rules from Representations. CoRR (2017)
Christoph Dann, Tor Lattimore, Emma Brunskill
UBEV - A More Practical Algorithm for Episodic RL with Near-Optimal PAC and Regret Guarantees. CoRR (2017)
Karan Goel, Christoph Dann, Emma Brunskill
Sample Efficient Policy Search for Optimal Stopping Domains. CoRR (2017)
Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. IEEE Trans. Pattern Anal. Mach. Intell. 39 (5) (2017)
Karan Goel, Christoph Dann, Emma Brunskill
Sample Efficient Policy Search for Optimal Stopping Domains. IJCAI (2017)
Markus R. Dann, Christoph Dann
Automated matching of pipeline corrosion features from in-line inspection data. Reliab. Eng. Syst. Saf. 162 (2017)
Christoph Dann, Tor Lattimore, Emma Brunskill
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning. NIPS (2017)
Christoph Dann, Katja Hofmann, Sebastian Nowozin
Memory Lens: How Much Memory Does an Agent Use? CoRR (2016)
Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill
Energetic Natural Gradient Descent. ICML (2016)
Alborz Geramifard, Christoph Dann, Robert H. Klein, William Dabney, Jonathan P. How
RLPy: a value-function-based reinforcement learning framework for education and research. J. Mach. Learn. Res. 16 (2015)
Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. CoRR (2015)
Christoph Dann, Gerhard Neumann, Jan Peters
Policy Evaluation with Temporal Differences: A Survey and Comparison (Extended Abstract). ICAPS (2015)
Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas, Eric P. Xing
The Human Kernel. CoRR (2015)
Christoph Dann, Emma Brunskill
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning. CoRR (2015)
Andrew Gordon Wilson, Christoph Dann, Hannes Nickisch
Thoughts on Massively Scalable Gaussian Processes. CoRR (2015)
Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas, Eric P. Xing
The Human Kernel. NIPS (2015)
Christoph Dann, Emma Brunskill
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning. NIPS (2015)
Christoph Dann, Gerhard Neumann, Jan Peters
Policy evaluation with temporal differences: a survey and comparison. J. Mach. Learn. Res. 15 (1) (2014)
Christoph Dann, Peter V. Gehler, Stefan Roth, Sebastian Nowozin
Pottics - The Potts Topic Model for Semantic Image Segmentation. DAGM/OAGM Symposium (2012)