| Learning to predict by the methods of temporal differences RS Sutton Machine learning 3 (1), 9-44, 1988 | 5391 | 1988 |
| What are the Main Risk Factors for Falls Amongst Older People and what are the Most Effective Interventions to Prevent These Falls?. C Todd, D Skelton World Health Organization, 2004 | 644* | 2004 |
| Exploiting structure to efficiently solve large scale partially observable Markov decision processes P Poupart University of Toronto, 2005 | 288 | 2005 |
| An analytic solution to discrete Bayesian reinforcement learning P Poupart, N Vlassis, J Hoey, K Regan Proceedings of the 23rd international conference on Machine learning, 697-704, 2006 | 280 | 2006 |
| Point-based value iteration for continuous POMDPs JM Porta, N Vlassis, MTJ Spaan, P Poupart Journal of Machine Learning Research 7 (Nov), 2329-2367, 2006 | 248 | 2006 |
| Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process J Hoey, P Poupart, A von Bertoldi, T Craig, C Boutilier, A Mihailidis Computer Vision and Image Understanding 114 (5), 503-519, 2010 | 237 | 2010 |
| Bounded finite state controllers P Poupart, C Boutilier Advances in neural information processing systems, 823-830, 2004 | 223 | 2004 |
| A decision-theoretic approach to task assistance for persons with dementia J Boger, P Poupart, J Hoey, C Boutilier, G Fernie, A Mihailidis IJCAI, 1293-1299, 2005 | 211 | 2005 |
| A planning system based on Markov decision processes to guide people with dementia through activities of daily living J Boger, J Hoey, P Poupart, C Boutilier, G Fernie, A Mihailidis IEEE Transactions on Information Technology in Biomedicine 10 (2), 323-333, 2006 | 201 | 2006 |
| Assisting persons with dementia during handwashing using a partially observable Markov decision process. J Hoey, A Von Bertoldi, P Poupart, A Mihailidis International Conference on Computer Vision Systems: Proceedings, 2007 | 169 | 2007 |
| Factored partially observable Markov decision processes for dialogue management JD Williams, P Poupart, S Young Proc. IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue …, 2005 | 146 | 2005 |
| Value-directed compression of POMDPs P Poupart, C Boutilier Advances in neural information processing systems, 1579-1586, 2003 | 143 | 2003 |
| Bayesian reputation modeling in e-marketplaces sensitive to subjectivity, deception and change K Regan, P Poupart, R Cohen Proceedings of the National Conference on Artificial Intelligence 21 (2), 1206, 2006 | 141 | 2006 |
| Constraint-based optimization and utility elicitation using the minimax decision criterion C Boutilier, R Patrascu, P Poupart, D Schuurmans Artificial Intelligence 170 (8-9), 686-713, 2006 | 137 | 2006 |
| Partially observable Markov decision processes with continuous observations for dialogue management JD Williams, P Poupart, S Young Recent Trends in Discourse and Dialogue, 191-217, 2008 | 130 | 2008 |
| Solving POMDPs with continuous or large discrete observation spaces J Hoey, P Poupart IJCAI, 1332-1338, 2005 | 126 | 2005 |
| 3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study J Dolz, C Desrosiers, IB Ayed NeuroImage 170, 456-470, 2018 | 122 | 2018 |
| Self-adaptive hierarchical sentence model H Zhao, Z Lu, P Poupart Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 120 | 2015 |
| VDCBPI: an approximate scalable algorithm for large POMDPs P Poupart, C Boutilier Advances in Neural Information Processing Systems, 1081-1088, 2005 | 111 | 2005 |
| Model-based Bayesian reinforcement learning in partially observable domains P Poupart, N Vlassis Proc Int. Symp. on Artificial Intelligence and Mathematics,, 1-2, 2008 | 82 | 2008 |
Martin WainwrightProfessor of EECS and Statistics, UC BerkeleyVerified email at berkeley.edu
