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Christoph Dann
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Unifying PAC and regret: Uniform PAC bounds for episodic reinforcement learning
C Dann, T Lattimore, E Brunskill
Advances in Neural Information Processing Systems, 5717-5727, 2017
3032017
Policy evaluation with temporal differences: a survey and comparison.
C Dann, G Neumann, J Peters
Journal of Machine Learning Research 15 (1), 809-883, 2014
2642014
Sample complexity of episodic fixed-horizon reinforcement learning
C Dann, E Brunskill
Advances in Neural Information Processing Systems, 2818-2826, 2015
2602015
Scaling up behavioral science interventions in online education
RF Kizilcec, J Reich, M Yeomans, C Dann, E Brunskill, G Lopez, S Turkay, ...
Proceedings of the National Academy of Sciences, 2020
1632020
Policy certificates: Towards accountable reinforcement learning
C Dann, L Li, W Wei, E Brunskill
International Conference on Machine Learning, 1507-1516, 2019
1532019
Thoughts on massively scalable Gaussian processes
AG Wilson, C Dann, H Nickisch
arXiv preprint arXiv:1511.01870, 2015
1122015
On Oracle-Efficient PAC RL with Rich Observations
C Dann, N Jiang, A Krishnamurthy, A Agarwal, J Langford, RE Schapire
Advances in Neural Information Processing Systems, 1429-1439, 2018
1072018
RLPy: a value-function-based reinforcement learning framework for education and research.
A Geramifard, C Dann, RH Klein, W Dabney, JP How
Journal of Machine Learning Research 16, 1573-1578, 2015
105*2015
The human kernel
AG Wilson, C Dann, C Lucas, EP Xing
Advances in Neural Information Processing Systems, 2854-2862, 2015
812015
Being optimistic to be conservative: Quickly learning a cvar policy
R Keramati, C Dann, A Tamkin, E Brunskill
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4436-4443, 2020
782020
Automated matching of pipeline corrosion features from in-line inspection data
MR Dann, C Dann
Reliability Engineering & System Safety 162, 40-50, 2017
502017
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL
A Pacchiano, C Dann, C Gentile, P Bartlett
arXiv preprint arXiv:2012.13045, 2020
412020
Bayesian time-of-flight for realtime shape, illumination and albedo
A Adam, C Dann, O Yair, S Mazor, S Nowozin
IEEE transactions on pattern analysis and machine intelligence 39 (5), 851-864, 2017
412017
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
C Dann, M Mohri, T Zhang, J Zimmert
Advances in Neural Information Processing Systems 34, 2021
37*2021
Dynamic balancing for model selection in bandits and rl
A Cutkosky, C Dann, A Das, C Gentile, A Pacchiano, M Purohit
International Conference on Machine Learning, 2276-2285, 2021
342021
A Model Selection Approach for Corruption Robust Reinforcement Learning
CY Wei, C Dann, J Zimmert
International Conference on Algorithmic Learning Theory, 2022
332022
Distributionally-aware exploration for cvar bandits
A Tamkin, R Keramati, C Dann, E Brunskill
NeurIPS 2019 Workshop on Safety and Robustness on Decision Making, 2019
332019
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation
C Dann, Y Mansour, M Mohri, A Sekhari, K Sridharan
International Conference on Machine Learning, 4666-4689, 2022
322022
Beyond value-function gaps: Improved instance-dependent regret bounds for episodic reinforcement learning
C Dann, TV Marinov, M Mohri, J Zimmert
Advances in Neural Information Processing Systems 34, 2021
272021
Energetic natural gradient descent
P Thomas, BC Silva, C Dann, E Brunskill
International Conference on Machine Learning, 2887-2895, 2016
222016
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