Christoph Dann

According to our database, Christoph Dann authored at least 46 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Conditioned 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, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent

CoRR, 2024

Rate-Preserving Reductions for Blackwell Approachability.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

CoRR, 2024

A Minimaximalist Approach to Reinforcement Learning from Human Feedback.

Gokul Swamy, Christoph Dann, Rahul Kidambi, Steven Wu, Alekh Agarwal

Proceedings of the Forty-first International Conference on Machine Learning, 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 Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Data-Driven Online Model Selection With Regret Guarantees.

Christoph Dann, Claudio Gentile, Aldo Pacchiano

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

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

Aldo Pacchiano, Christoph Dann, Claudio Gentile

CoRR, 2023

Best of Both Worlds Policy Optimization.

Christoph Dann, Chen-Yu Wei, Julian Zimmert

Proceedings of the International Conference on Machine Learning, 2023

Reinforcement Learning Can Be More Efficient with Multiple Rewards.

Christoph Dann, Yishay Mansour, Mehryar Mohri

Proceedings of the International Conference on Machine Learning, 2023

Learning in POMDPs is Sample-Efficient with Hindsight Observability.

Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang

Proceedings of the International Conference on Machine Learning, 2023

A Blackbox Approach to Best of Both Worlds in Bandits and Beyond.

Christoph Dann, Chen-Yu Wei, Julian Zimmert

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

A Unified Algorithm for Stochastic Path Problems.

Christoph Dann, Chen-Yu Wei, Julian Zimmert

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Pseudonorm Approachability and Applications to Regret Minimization.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Multiple-policy High-confidence Policy Evaluation.

Christoph Dann, Mohammad Ghavamzadeh, Teodor V. Marinov

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Best of Both Worlds Model Selection.

Aldo Pacchiano, Christoph Dann, Claudio Gentile

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.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

Proceedings of the International Conference on Machine Learning, 2022

Same Cause; Different Effects in the Brain.

Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

A Model Selection Approach for Corruption Robust Reinforcement Learning.

Chen-Yu Wei, Christoph Dann, Julian Zimmert

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Leveraging Initial Hints for Free in Stochastic Linear Bandits.

Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Qiuyi (Richard) Zhang

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

Neural Active Learning with Performance Guarantees.

Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile

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.

Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

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.

Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

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.

Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

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.

Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Strategic Exploration in Reinforcement Learning - New Algorithms and Learning Guarantees.

Christoph Dann

PhD thesis, 2020

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

Aldo Pacchiano, Christoph Dann, Claudio Gentile, Peter L. Bartlett

CoRR, 2020

Reinforcement Learning with Feedback Graphs.

Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

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.

Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Policy Certificates: Towards Accountable Reinforcement Learning.

Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

On Polynomial Time PAC Reinforcement Learning with Rich Observations.

Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

CoRR, 2018

On Oracle-Efficient PAC RL with Rich Observations.

Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

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.

Philip S. Thomas, Christoph Dann, Emma Brunskill

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Automated matching of pipeline corrosion features from in-line inspection data.

Markus R. Dann, Christoph Dann

Reliab. Eng. Syst. Saf., 2017

Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo.

Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Decoupling Learning Rules from Representations.

Philip S. Thomas, Christoph Dann, Emma Brunskill

CoRR, 2017

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

Christoph Dann, Tor Lattimore, Emma Brunskill

CoRR, 2017

Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning.

Christoph Dann, Tor Lattimore, Emma Brunskill

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.

Karan Goel, Christoph Dann, Emma Brunskill

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Memory Lens: How Much Memory Does an Agent Use?

Christoph Dann, Katja Hofmann, Sebastian Nowozin

CoRR, 2016

Energetic Natural Gradient Descent.

Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill

Proceedings of the 33nd International Conference on Machine Learning, 2016

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

J. Mach. Learn. Res., 2015

Thoughts on Massively Scalable Gaussian Processes.

Andrew Gordon Wilson, Christoph Dann, Hannes Nickisch

CoRR, 2015

The Human Kernel.

Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas, Eric P. Xing

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.

Christoph Dann, Emma Brunskill

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).

Christoph Dann, Gerhard Neumann, Jan Peters

Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, 2015

2014

Policy evaluation with temporal differences: a survey and comparison.

Christoph Dann, Gerhard Neumann, Jan Peters

J. Mach. Learn. Res., 2014

2012

Pottics - The Potts Topic Model for Semantic Image Segmentation.

Christoph Dann, Peter V. Gehler, Stefan Roth, Sebastian Nowozin

Proceedings of the Pattern Recognition, 2012