Dann, Christoph

35 publications

ICML 2025 Can RLHF Be More Efficient with Imperfect Reward Models? a Policy Coverage Perspective Jiawei Huang, Bingcong Li, Christoph Dann, Niao He

ICLRW 2025 Can RLHF Be More Efficient with Imperfect Reward Models? a Policy Coverage Perspective Jiawei Huang, Bingcong Li, Christoph Dann, Niao He

ICML 2025 Design Considerations in Offline Preference-Based RL Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov

TMLR 2025 Preserving Expert-Level Privacy in Offline Reinforcement Learning Navodita Sharma, Vishnu Vinod, Abhradeep Guha Thakurta, Alekh Agarwal, Borja Balle, Christoph Dann, Aravindan Raghuveer

NeurIPS 2025 Principled Model Routing for Unknown Mixtures of Source Domains Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri

COLT 2025 Rate-Preserving Reductions for Blackwell Approachability Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

ICML 2024 A Minimaximalist Approach to Reinforcement Learning from Human Feedback Gokul Swamy, Christoph Dann, Rahul Kidambi, Steven Wu, Alekh Agarwal

NeurIPSW 2024 Conditional Language Policy: A General Framework for Steerable Multi-Objective Finetuning Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Kumar Avinava Dubey, Alexandre Rame, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Leonard Hussenot, Olivier Bachem, Edouard Leurent

NeurIPSW 2024 Domain Adaptation for Robust Model Routing Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri

NeurIPSW 2024 P3O: Pessimistic Preference-Based Policy Optimization for Robust Alignment from Preferences Dhawal Gupta, Christoph Dann, Alekh Agarwal

ALT 2023 A Unified Algorithm for Stochastic Path Problems Christoph Dann, Chen-Yu Wei, Julian Zimmert

ICML 2023 Best of Both Worlds Policy Optimization Christoph Dann, Chen-Yu Wei, Julian Zimmert

ICML 2023 Learning in POMDPs Is Sample-Efficient with Hindsight Observability Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang

ALT 2023 Pseudonorm Approachability and Applications to Regret Minimization Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balubramanian Sivan

ICML 2023 Reinforcement Learning Can Be More Efficient with Multiple Rewards Christoph Dann, Yishay Mansour, Mehryar Mohri

ALT 2022 A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei, Christoph Dann, Julian Zimmert

NeurIPS 2022 Best of Both Worlds Model Selection Aldo Pacchiano, Christoph Dann, Claudio Gentile

CLeaR 2022 Same Cause; Different Effects in the Brain Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe

NeurIPS 2021 A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

NeurIPS 2021 Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

NeurIPS 2021 Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

ICML 2021 Dynamic Balancing for Model Selection in Bandits and RL Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit

NeurIPS 2021 Neural Active Learning with Performance Guarantees Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile

AAAI 2020 Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill

NeurIPS 2020 Reinforcement Learning with Feedback Graphs Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

ICML 2019 Policy Certificates: Towards Accountable Reinforcement Learning Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill

ICML 2018 Decoupling Gradient-like Learning Rules from Representations Philip Thomas, Christoph Dann, Emma Brunskill

NeurIPS 2018 On Oracle-Efficient PAC RL with Rich Observations Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

IJCAI 2017 Sample Efficient Policy Search for Optimal Stopping Domains Karan Goel, Christoph Dann, Emma Brunskill

NeurIPS 2017 Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning Christoph Dann, Tor Lattimore, Emma Brunskill

ICML 2016 Energetic Natural Gradient Descent Philip Thomas, Bruno Castro Silva, Christoph Dann, Emma Brunskill

MLOSS 2015 RLPy: A Value-Function-Based Reinforcement Learning Framework for Education and Research Alborz Geramifard, Christoph Dann, Robert H. Klein, William Dabney, Jonathan P. How

NeurIPS 2015 Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning Christoph Dann, Emma Brunskill

NeurIPS 2015 The Human Kernel Andrew G Wilson, Christoph Dann, Chris Lucas, Eric P Xing

JMLR 2014 Policy Evaluation with Temporal Differences: A Survey and Comparison Christoph Dann, Gerhard Neumann, Jan Peters