Publications in Venue "ICML"
| 1. | J. Wen, R. Greiner, D. Schuurmans. "Domain Aggregation Networks for Multi-Source Domain Adaptation". International Conference on Machine Learning (ICML), July 2020.  |
| 2. | J. Foerster, H. Song, E. Hughes, N. Burch, I. Dunning, S. Whiteson, M. Botvinick, M. Bowling. "Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning". International Conference on Machine Learning (ICML), (ed: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), pp 1942-1951, June 2019.  |
| 3. | L. Mou, Z. Lu, H. Li, Z. Jin. "Coupling Distributed and Symbolic Execution for Natural Language Queries". International Conference on Machine Learning (ICML), pp 2518-2526, July 2018. |
| 4. | E. Imani, M. White. "Improving Regression Performance with Distributional Losses". International Conference on Machine Learning (ICML), (ed: Jennifer G. Dy, Andreas Krause), pp 2162-2171, July 2018. |
| 5. | Y. Pan, A. Farahmand, M. White, S. Nabi, P. Grover, D. Nikovski. "Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control". International Conference on Machine Learning (ICML), (ed: Jennifer G. Dy, Andreas Krause), pp 3983-3992, July 2018. |
| 6. | M. Machado, M. Bellemare, M. Bowling. "A Laplacian framework for option discovery in reinforcement learning". International Conference on Machine Learning (ICML), (ed: Doina Precup, Yee Whye Teh), pp 2295-2304, August 2017. |
| 7. | M. Schlegel, Y. Pan, J. Chen, M. White. "Adapting Kernel Representations Online Using Submodular Maximization". International Conference on Machine Learning (ICML), (ed: Doina Precup, Yee Whye Teh), pp 3037-3046, August 2017. |
| 8. | M. White. "Unifying Task Specification in Reinforcement Learning". International Conference on Machine Learning (ICML), (ed: Doina Precup, Yee Whye Teh), pp 3742-3750, August 2017. |
| 9. | S. Ravanbakhsh, B. Poczos, R. Greiner. "Boolean matrix factorization and noisy completion via message passing". International Conference on Machine Learning (ICML), (ed: Maria Florina Balcan, Kilian Q. Weinberger), pp 945-954, June 2016. |
| 10. | J. Neufeld, A. Gyorgy, C. Szepesvari, D. Schuurmans. "Adaptive Monte Carlo via bandit allocation". International Conference on Machine Learning (ICML), (ed: Eric P. Xing, Tony Jebara), pp 1944-1952, June 2014. |
| 11. | S. Ravanbakhsh, R. Greiner, B. Frey, C. Srinivasa. "Min-Max Problems on Factor-Graphs". International Conference on Machine Learning (ICML), pp 1035-1043, June 2014. |
| 12. | J. Wen, C. Yu, R. Greiner. "Robust Learning Under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification". International Conference on Machine Learning (ICML), pp 631-639, June 2014. |
| 13. | A. Afkanpour, A. Gyorgy, C. Szepesvari, M. Bowling. "A randomized mirror descent algorithm for large scale multiple kernel learning". International Conference on Machine Learning (ICML), pp 374–382, June 2013. |
| 14. | M. Bellemare, J. Veness, M. Bowling. "Bayesian learning of recursively factored environments". International Conference on Machine Learning (ICML), pp 1211–1219, June 2013. |
| 15. | Y. Yu, H. Cheng, D. Schuurmans, C. Szepesvari. "Characterizing the representer theorem". International Conference on Machine Learning (ICML), (ed: Sanjoy Dasgupta, David McAllester), pp 570-578, June 2013. |
| 16. | S. Ravanbakhsh, C. Yu, R. Greiner. "A Generalized Loop Correction Method for Approximate Inference in Graphical Models". International Conference on Machine Learning (ICML), (ed: John Langford, Joelle Pineau), pp 543-550, July 2012. |
| 17. | T. Degris, M. White, R. Sutton. "Linear Off-Policy Actor-Critic". International Conference on Machine Learning (ICML), pp n/a, June 2012. |
| 18. | L. Li, B. Poczos, C. Szepesvari, R. Greiner. "Budgeted Distribution Learning of Belief Net Parameters". International Conference on Machine Learning (ICML), June 2010. |
| 19. | L. Li, B. Poczos, C. Szepesvari, R. Greiner. "Budgeted Distribution Learning in Parametric Models". International Conference on Machine Learning (ICML), April 2010. |
| 20. | A. Farhangfar, R. Greiner, C. Szepesvari. " Learning to Segment from a Few Well-Selected Training Images". International Conference on Machine Learning (ICML), June 2009. |
| 21. | L. Xu, M. White, D. Schuurmans. " Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning". International Conference on Machine Learning (ICML), June 2009. |
| 22. | B. Poczos, Y. Abbasi-Yadkori, C. Szepesvari, R. Greiner, N. Sturtevant. "Learning when to stop thinking and do something!". International Conference on Machine Learning (ICML), June 2009. |
| 23. | S. Kirshner, B. Poczos. "ICA and ISA Using Schweizer-Wolff Measure of Dependence". International Conference on Machine Learning (ICML), July 2008. |
| 24. | M. Bowling, M. Johanson, N. Burch, D. Szafron. "Strategy Evaluation in Extensive Games with Importance Sampling". International Conference on Machine Learning (ICML), (ed: Andrew McCallum and Sam Roweis), pp 72--79, July 2008. |
| 25. | S. Gelly, D. Silver. "Combining Online and Offline Knowledge in UCT". International Conference on Machine Learning (ICML), August 2007. |
| 26. | M. Ghavamzadeh, Y. Engel. " Bayesian Actor-Critic Algorithms". International Conference on Machine Learning (ICML), pp 297-304, June 2007. |
| 27. | S. Kirshner, P. Smyth. "Infinite Mixtures of Trees". International Conference on Machine Learning (ICML), June 2007. |
| 28. | R. Sutton, A. Koop, D. Silver. "On the Role of Tracking in Stationary Environments". International Conference on Machine Learning (ICML), April 2007. |
| 29. | A. Farahmand, J. Audibert, C. Szepesvari. "Manifold-Adaptive Dimension Estimation". International Conference on Machine Learning (ICML), March 2007. |
| 30. | N. Ratliff, J. Bagnell, M. Zinkevich. "Maximum Margin Planning". International Conference on Machine Learning (ICML), Pittsburgh, August 2006. |
| 31. | C. Lee, R. Greiner, S. Wang. "Using Query-Specific Variance Estimates to Combine Bayesian Classifiers". International Conference on Machine Learning (ICML), Pittsburgh, June 2006. |
| 32. | L. Xu, D. Wilkinson, F. Southey, D. Schuurmans. "Discriminative Unsupervised Learning of Structured Predictors". International Conference on Machine Learning (ICML), Pittsburgh, January 2006. |
| 33. | M. Bowling, P. McCracken, M. James, J. Neufeld, D. Wilkinson. "Learning predictive state representations using non-blind policies". International Conference on Machine Learning (ICML), Pittsburgh, pp 129-136, January 2006. |
| 34. | S. Wang, S. Wang, R. Greiner, D. Schuurmans, L. Cheng. "Exploiting Syntactic, Semantic and Lexical Regularities in Language Modeling via Directed Markov Random Fields". International Conference on Machine Learning (ICML), Bonn, Germany, pp 953-960, August 2005.  |
| 35. | B. Tanner, R. Sutton. "TD(lambda) Networks: Temporal-Difference Networks With Eligibility Traces". International Conference on Machine Learning (ICML), Bonn, Germany, August 2005. |
| 36. | M. Bowling, A. Ghodsi, D. Wilkinson. "Action respecting embedding". International Conference on Machine Learning (ICML), Bonn, Germany, pp 65-72, January 2005. |
| 37. | T. Wang, D. Lizotte, M. Bowling, D. Schuurmans. "Bayesian Sparse Sampling for On-Line Reward Optimization". International Conference on Machine Learning (ICML), Bonn, Germany, pp 961-968, January 2005. |
| 38. | C. Szepesvari, R. Munos. "Finite Time Bounds for Sampling Based Fitted Value Iteration". International Conference on Machine Learning (ICML), Bonn, Germany, pp 881-886, January 2005. |
| 39. | L. Cheng, F. Jiao, D. Schuurmans, S. Wang. "Variational Bayesian Image Modelling". International Conference on Machine Learning (ICML), Bonn, Germany, January 2005. |
| 40. | R. Greiner, D. Schuurmans. "ICML 2004 Conference Proceedings". International Conference on Machine Learning (ICML), July 2004. |
| 41. | C. Szepesvari, W. Smart. "Interpolation-based Q-learning". International Conference on Machine Learning (ICML), pp 791-798, January 2004. |
| 42. | M. Ghavamzadeh, S. Mahadevan. "Hierarchical Policy Gradient Algorithms". International Conference on Machine Learning (ICML), Washington, DC USA, pp 226-233, August 2003. |
| 43. | S. Wang, D. Schuurmans, F. Peng, Y. Zhao. "Learning mixture models with the regularized latent maximum entropy principle". International Conference on Machine Learning (ICML), Washington, DC USA, August 2003. |
| 44. | C. Guestrin, R. Patrascu, D. Schuurmans. "Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs". International Conference on Machine Learning (ICML), Sydney Australia, July 2002. |
| 45. | M. Ghavamzadeh, S. Mahadevan. "Hierarchically Optimal Average Reward Reinforcement Learning". International Conference on Machine Learning (ICML), Sydney Australia, pp 195-202, July 2002. |
| 46. | T. Van Allen, R. Greiner. "Model Selection Criteria for Learning Belief Nets: An Empirical Comparison". International Conference on Machine Learning (ICML), Sydney Australia, June 2002. |
| 47. | M. Ghavamzadeh, S. Mahadevan. "Continuous-Time Hierarchical Reinforcement Learning". International Conference on Machine Learning (ICML), Williams College, pp 186-193, July 2001. |
| 48. | M. Bowling, M. Veloso. "Convergence of Gradient Dynamics with a Variable Learning Rate". International Conference on Machine Learning (ICML), Williams College, pp 27-34, June 2001. |
| 49. | D. Precup, R. Sutton, S. Dasgupta. "Off-Policy Temporal-Difference Learning With Function Approximation". International Conference on Machine Learning (ICML), Williams College, pp 417-424, January 2001. |
| 50. | P. Stone, R. Sutton. "Scaling Reinforcement Learning Toward RoboCup Soccer". International Conference on Machine Learning (ICML), Williams College, January 2001. |
| 51. | T. Van Allen, R. Greiner. "A Model Selection Criteria for Learning Belief Nets: An Empirical Comparison". International Conference on Machine Learning (ICML), Stanford University, July 2000. |
| 52. | D. Schuurmans, F. Southey. "An adaptive regularization criterion for supervised learning". International Conference on Machine Learning (ICML), Stanford University, June 2000. |
| 53. | M. Bowling. "Convergence Problems of General-Sum Multiagent Reinforcement Learning". International Conference on Machine Learning (ICML), Stanford University, pp 89-94, June 2000. |
| 54. | D. Precup, R. Sutton, S. Singh. "Eligibility Traces for Off-Policy Policy Evaluation". International Conference on Machine Learning (ICML), Stanford University, pp 759-766, January 2000. |
| 55. | C. Drummond, R. Holte. "Exploiting the Cost (In) Sensitivity of Decision Tree Splitting Criteria". International Conference on Machine Learning (ICML), Stanford University, pp 239-246, January 2000. |
| 56. | R. Sutton, D. Precup, S. Singh. "Intra-Option Learning About Temporally Abstract Actions". International Conference on Machine Learning (ICML), Madison, Wisconsin USA, pp 556-564, January 1998. |
| 57. | D. Precup, R. Sutton. "Exponentiated Gradient Methods for Reinforcement Learning". International Conference on Machine Learning (ICML), Nashville, pp 272-277, July 1997. |
| 58. | D. Precup, R. Sutton. "Multi-Time Models for Reinforcement Learning". International Conference on Machine Learning (ICML), Nashville, July 1997. |
| 59. | T. Scheffer, R. Greiner, C. Darken. "Why Experimentation can be better than `Perfect Guidance'". International Conference on Machine Learning (ICML), Nashville, July 1997. |
| 60. | D. Schuurmans, L. Ungar, D. Foster. "Characterizing the Generalization Performance of Model Selection Strategies". International Conference on Machine Learning (ICML), Nashville, January 1997. |
| 61. | R. Greiner, A. Grove, A. Kogan. "Exploiting the Omission of Irrelevant Data". International Conference on Machine Learning (ICML), pp 207-215, July 1996. |
| 62. | R. Greiner, A. Grove, D. Roth. "Learning Active Classifiers". International Conference on Machine Learning (ICML), pp 207-215, July 1996. |
| 63. | R. Greiner. "The Challenge of Revising an Impure Theory". International Conference on Machine Learning (ICML), pp 268-277, July 1995. |
| 64. | R. Sutton. "TD Models: Modeling the World at a Mixture of Time Scales". International Conference on Machine Learning (ICML), pp 531-539, January 1995. |
| 65. | P. Auer, R. Holte, W. Maass. "Theory and Applications of Agnostic PAC-Learning With Small Decision Trees". International Conference on Machine Learning (ICML), pp 21-29, January 1995. |
| 66. | R. Sutton, S. Whitehead. "Online Learning With Random Representations". International Conference on Machine Learning (ICML), Amherst, MA, USA, (ed: M. Kaufmann), pp 314-321, January 1993. |
| 67. | P. Clark, R. Holte. "Lazy Partial Evaluation: An Integration of Explanation-Based Generalisation and Partial Evaluation". International Conference on Machine Learning (ICML), pp 82-91, January 1992. |
| 68. | R. Sutton. "Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming". International Conference on Machine Learning (ICML), Austin, Texas, USA, pp 216-224, January 1990. |
