Stéphane Ross - Robotics Institute

A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes. [pdf]
S. Ross, J. Pineau, B. Chaib-draa & P. Kreitmann
In Journal of Machine Learning Research (JMLR), vol. 12, p. 1729-1770, 2011.
Online Planning Algorithms for POMDPs. [pdf]
S. Ross, J. Pineau, S. Paquet & B. Chaib-draa
In Journal of Artificial Intelligence Research (JAIR), vol. 32, p. 663-704, 2008.

Normalized Online Learning. [pdf]
S. Ross, P. Mineiro & J. Langford
In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligenc (UAI), 2013.
Learning Policies for Contextual Submodular Prediction. [pdf] [proofs (pdf)]
S. Ross, J. Zhou, Y. Yue, D. Dey & J. A. Bagnell
In Proceedings of the 30th International Conference on Machine Learning (ICML), 2013.
Learning Monocular Reactive UAV Control in Cluttered Natural Environments. [arXiv]
S. Ross, N. Melik-Barkhudarov, K. S. Shankar, A. Wendel, D. Dey, J. A. Bagnell & M. Hebert
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2013.
Agnostic System Identification for Model-Based Reinforcement Learning. [pdf] [supplementary material (pdf)] [talk]
S. Ross & J. A. Bagnell.
In Proceedings of the 29th International Conference on Machine Learning (ICML), 2012.
Learning Message-Passing Inference Machines for Structured Prediction. [pdf] [poster (pdf)]
S. Ross, D. Munoz, M. Hebert & J. A. Bagnell.
In Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning. [pdf] [slides (pdf)] [talk]
S. Ross, G. J. Gordon & J. A. Bagnell.
In Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS), 2011.
Efficient Reductions for Imitation Learning. [pdf] [supplementary material (pdf)]
S. Ross & J. A. Bagnell.
In Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS), 2010.
Sensitivity Analysis of POMDP Value Functions. [pdf]
S. Ross, M. Izadi, M. Mercer & D. Buckeridge.
In Proceedings of the 8th International Conference on Machine Learning and Applications (ICMLA), 2009.
Bayesian Reinforcement Learning in POMDPs with Gaussian Processes. [pdf]
P. Dallaire, C. Besse, S. Ross & B. Chaib-draa.
In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2009.
Model-Based Bayesian Reinforcement Learning in Large Structured Domains. [pdf]
S. Ross & J. Pineau.
In Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI), 2008.
Bayesian Reinforcement Learning in Continuous POMDPs with Application to Robot Navigation. [pdf] [slides (pdf)]
S. Ross, B. Chaib-draa & J. Pineau.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2008.
Bayes-Adaptive POMDPs. [pdf] [Proofs (pdf)]
S. Ross, B. Chaib-draa & J. Pineau.
In Advances in Neural Information Processing Systems 20 (NIPS), 2008.
Theoretical Analysis of Heuristic Search Methods for Online POMDPs. [pdf]
S. Ross, J. Pineau & B. Chaib-draa.
In Advances in Neural Information Processing Systems 20 (NIPS), 2008.
AEMS : An Anytime Online Search Algorithm for Approximate Policy Refinement in Large POMDPs. [pdf]
S. Ross & B. Chaib-draa.
In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI), 2007.
Satisfaction Equilibrium : Achieving Cooperation in Incomplete Information Games. [pdf] [slides (ppt)]
S. Ross & B. Chaib-draa.
In Proceedings of the 19th Canadian Conference on Artificial Intelligence (CanAI), 2006.

Bayes-Adaptive POMDPs: A New Perspective on the Explore-Exploit Tradeoff in Partially Observable Domains. [pdf]
J. Pineau, S. Ross & B. Chaib-draa.
In Proceedings of the 10th Symposium on Artificial Intelligence and Mathematics (ISAIM), 2008.
Online Policy Improvement in Large POMDPs via an Error Minimization Search. [pdf] [slides (pdf)]
S. Ross, J. Pineau & B. Chaib-draa.
In Proceedings of the 2nd North East Student Colloquium on Artificial Intelligence (NESCAI), 2007.
Learning to Play a Satisfaction Equilibrium. [pdf]
S. Ross & B. Chaib-draa.
In Proceedings of the Workshop on Evolutionary Models of Collaboration (EMC), 2007.
Hybrid POMDP Algorithms. [pdf]
S. Paquet, B. Chaib-draa & S. Ross.
In Proceedings of The Workshop on Multi-Agent Sequential Decision Making in Uncertain Domains (MSDM), 2006.

Learning Monocular Reactive UAV Control in Cluttered Natural Environments. [arXiv]
S. Ross, N. Melik-Barkhudarov, K. S. Shankar, A. Wendel, D. Dey, J. A. Bagnell & M. Hebert
ArXiv 1211.1690, 2012.
Agnostic System Identification for Model-Based Reinforcement Learning. [arXiv]
S. Ross & J. A. Bagnell.
ArXiv 1203.1007, 2012.
Stability Conditions for Online Learnability. [arXiv]
S. Ross & J. A. Bagnell.
ArXiv 1108.3154, 2011.
Bayes-Adaptive POMDPs. [pdf]
S. Ross, B. Chaib-draa & J. Pineau.
Technical Report SOCS-TR-2007.6. McGill University, 2007. (Longer version of the similarly titled NIPS paper).
Report on Satisfaction Equilibria. [pdf]
S. Ross & B. Chaib-draa.
2006.

Interactive Learning for Sequential Decisions and Predictions. [pdf]
S. Ross.
Ph.D. Thesis, Carnegie Mellon University, 2013.
Model-Based Bayesian Reinforcement Learning in Complex Domains. [pdf]
S. Ross.
M.Sc. Thesis, McGill University, 2008.