Pascal Poupart

Pascal Poupart, Craig Boutilier: Vector-space Analysis of Belief-state Approximation for POMDPs. CoRR abs/1301.2304 (2013)

Pascal Poupart, Luis E. Ortiz, Craig Boutilier: Value-Directed Sampling Methods for POMDPs. CoRR abs/1301.2305 (2013)

Pascal Poupart, Craig Boutilier: Value-Directed Belief State Approximation for POMDPs. CoRR abs/1301.3887 (2013)

Jason D. Williams, Kai Yu, Brahim Chaib-draa, Oliver Lemon, Roberto Pieraccini, Olivier Pietquin, Pascal Poupart, Steve Young: Introduction to the Issue on Advances in Spoken Dialogue Systems and Mobile Interface. J. Sel. Topics Signal Processing 6(8): 889-890 (2012)

Jesse Hoey, Craig Boutilier, Pascal Poupart, Patrick Olivier, Andrew Monk, Alex Mihailidis: People, sensors, decisions: Customizable and adaptive technologies for assistance in healthcare. TiiS 2(4): 20 (2012)

Aditya Tayal, Pascal Poupart, Yuying Li: Hierarchical Double Dirichlet Process Mixture of Gaussian Processes. AAAI 2012

Meena Abdelmaseeh, Pascal Poupart, Benn Smith, Daniel W. Stashuk: Muscle Categorization Using Quantitative Needle Electromyography: A 2-Stage Gaussian Mixture Model Based Approach. ICMLA (1) 2012: 548-553

Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting: Symbolic Dynamic Programming for Continuous State and Observation POMDPs. NIPS 2012: 1403-1411

Dongho Kim, Kee-Eung Kim, Pascal Poupart: Cost-Sensitive Exploration in Bayesian Reinforcement Learning. NIPS 2012: 3077-3085

Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine: Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker. CoRR abs/1203.3500 (2012)

Marc Toussaint, Laurent Charlin, Pascal Poupart: Hierarchical POMDP Controller Optimization by Likelihood Maximization. CoRR abs/1206.3291 (2012)

Wei Li, Pascal Poupart, Peter van Beek: Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference. J. Artif. Intell. Res. (JAIR) 40: 729-765 (2011)

Mathieu Sinn, Pascal Poupart: Asymptotic Theory for Linear-Chain Conditional Random Fields. Journal of Machine Learning Research - Proceedings Track 15: 679-687 (2011)

James Yungjen Tung, Jonathan F. L. Semple, Wei X. Woo, Wei-Shou Hsu, Mathieu Sinn, Eric A. Roy, Pascal Poupart: Ambulatory Assessment of Lifestyle Factors for Alzheimer's Disease and Related Dementias. AAAI Spring Symposium: Computational Physiology 2011

Pascal Poupart, Kee-Eung Kim, Dongho Kim: Closing the Gap: Improved Bounds on Optimal POMDP Solutions. ICAPS 2011

Mathieu Sinn, Pascal Poupart: Smart walkers!: enhancing the mobility of the elderly. AAMAS 2011: 1133-1134

Pascal Poupart, Tobias Lang, Marc Toussaint: Escaping local optima in POMDP planning as inference. AAMAS 2011: 1263-1264

Muhammad Bilal Sheikh, Umar Farooq Minhas, Omar Zia Khan, Ashraf Aboulnaga, Pascal Poupart, David J. Taylor: A bayesian approach to online performance modeling for database appliances using gaussian models. ICAC 2011: 121-130

Mathieu Sinn, Pascal Poupart: Error Bounds for Online Predictions of Linear-Chain Conditional Random Fields: Application to Activity Recognition for Users of Rolling Walkers. ICMLA (2) 2011: 1-6

Robby Goetschalckx, Pascal Poupart, Jesse Hoey: Continuous Correlated Beta Processes. IJCAI 2011: 1269-1274

Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart: Point-Based Value Iteration for Constrained POMDPs. IJCAI 2011: 1968-1974

Omar Zia Khan, Pascal Poupart, John Mark Agosta: Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints. NIPS 2011: 2591-2599

Pascal Poupart, Tobias Lang, Marc Toussaint: Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains. ECML/PKDD (2) 2011: 613-628

Jesse Hoey, Pascal Poupart, Axel von Bertoldi, Tammy Craig, Craig Boutilier, Alex Mihailidis: Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process. Computer Vision and Image Understanding 114(5): 503-519 (2010)

Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine: Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker. UAI 2010: 392-400

Pascal Poupart: Bayesian Reinforcement Learning. Encyclopedia of Machine Learning 2010: 90-93

Pascal Poupart: Partially Observable Markov Decision Processes. Encyclopedia of Machine Learning 2010: 754-760

Razvan C. Bunescu, Vitor R. Carvalho, Jan Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H. Göker, Hans W. Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker, Wolfgang Ketter, Alfred Kobsa, Sven Koenig, Tessa A. Lau, Lundy Lewis, Eric T. Matson, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Joelle Pineau, Pascal Poupart, Anita Raja, Wheeler Ruml, Norman M. Sadeh, Guy Shani, Daniel G. Shapiro, Sarabjot Singh Anand, Matthew E. Taylor, Kiri Wagstaff, Trey Smith, William E. Walsh, Ron Zhou: AAAI 2008 Workshop Reports. AI Magazine 30(1): 108-118 (2009)

Omar Zia Khan, Pascal Poupart, James P. Black: Minimal Sufficient Explanations for Factored Markov Decision Processes. ICAPS 2009

Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal Poupart, John S. Zelek: Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images. CRV 2009: 53-60

Omar Zia Khan, Pascal Poupart, James P. Black: Minimal Sufficient Explanations for MDPs. ExaCt 2009: 48-59

Wei Li, Pascal Poupart, Peter van Beek: Exploiting Causal Independence Using Weighted Model Counting. AAAI 2008: 337-343

Guy Shani, Pascal Poupart, Ronen I. Brafman, Solomon Eyal Shimony: Efficient ADD Operations for Point-Based Algorithms. ICAPS 2008: 330-337

Omar Zia Khan, Pascal Poupart, James P. Black: Explaining recommendations generated by MDPs. ExaCt 2008: 13-24

Pascal Poupart, Nikos A. Vlassis: Model-based Bayesian Reinforcement Learning in Partially Observable Domains. ISAIM 2008

Marc Toussaint, Laurent Charlin, Pascal Poupart: Hierarchical POMDP Controller Optimization by Likelihood Maximization. UAI 2008: 562-570

Taehyun Park, Edward Lank, Pascal Poupart, Michael A. Terry: Is the sky pure today? AwkChecker: an assistive tool for detecting and correcting collocation errors. UIST 2008: 121-130

Andy Chiu, Pascal Poupart, Chrysanne DiMarco: Generating Lexical Analogies Using Dependency Relations. EMNLP-CoNLL 2007: 561-570

Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans: Constraint-based optimization and utility elicitation using the minimax decision criterion. Artif. Intell. 170(8-9): 686-713 (2006)

Wolfgang Achtner, Esma Aïmeur, Sarabjot Singh Anand, Doug Appelt, Naveen Ashish, Tiffany Barnes, Joseph E. Beck, M. Bernardine Dias, Prashant Doshi, Chris Drummond, William Elazmeh, Ariel Felner, Dayne Freitag, Hector Geffner, Christopher W. Geib, Richard Goodwin, Robert C. Holte, Frank Hutter, Fair Isaac, Nathalie Japkowicz, Gal A. Kaminka, Sven Koenig, Michail G. Lagoudakis, David B. Leake, Lundy Lewis, Hugo Liu, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Pascal Poupart, David V. Pynadath, Thomas Roth-Berghofer, Wheeler Ruml, Stefan Schulz, Sven Schwarz, Stephanie Seneff, Amit P. Sheth, Ron Sun, Michael Thielscher, Afzal Upal, Jason D. Williams, Steve Young, Dmitry Zelenko: Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program. AI Magazine 27(4): 92-102 (2006)

Josep M. Porta, Nikos A. Vlassis, Matthijs T. J. Spaan, Pascal Poupart: Point-Based Value Iteration for Continuous POMDPs. Journal of Machine Learning Research 7: 2329-2367 (2006)

Jennifer Boger, Jesse Hoey, Pascal Poupart, Craig Boutilier, Geoff Fernie, Alex Mihailidis: A Planning System Based on Markov Decision Processes to Guide People With Dementia Through Activities of Daily Living. IEEE Transactions on Information Technology in Biomedicine 10(2): 323-333 (2006)

Wei Li, Peter van Beek, Pascal Poupart: Performing Incremental Bayesian Inference by Dynamic Model Counting. AAAI 2006: 1173-1179

Kevin Regan, Pascal Poupart, Robin Cohen: Bayesian Reputation Modeling in E-Marketplaces Sensitive to Subjectivity, Deception and Change. AAAI 2006: 1206-1212

Tao Wang, Pascal Poupart, Michael H. Bowling, Dale Schuurmans: Compact, Convex Upper Bound Iteration for Approximate POMDP Planning. AAAI 2006: 1245-1252

Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevin Regan: An analytic solution to discrete Bayesian reinforcement learning. ICML 2006: 697-704

Laurent Charlin, Pascal Poupart, Romy Shioda: Automated Hierarchy Discovery for Planning in Partially Observable Environments. NIPS 2006: 225-232

Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans: Regret-based Utility Elicitation in Constraint-based Decision Problems. IJCAI 2005: 929-934

Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff Fernie, Alex Mihailidis: A Decision-Theoretic Approach to Task Assistance for Persons with Dementia. IJCAI 2005: 1293-1299

Jesse Hoey, Pascal Poupart: Solving POMDPs with Continuous or Large Discrete Observation Spaces. IJCAI 2005: 1332-1338

Kevin Regan, Robin Cohen, Pascal Poupart: The Advisor-POMDP: A Principled Approach to Trust through Reputation in Electronic Markets. PST 2005

Pascal Poupart, Craig Boutilier: VDCBPI: an Approximate Scalable Algorithm for Large POMDPs. NIPS 2004

Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans: Constraint-Based Optimization with the Minimax Decision Criterion. CP 2003: 168-182

Pascal Poupart, Craig Boutilier: Bounded Finite State Controllers. NIPS 2003

Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier, Carlos Guestrin: Greedy Linear Value-Approximation for Factored Markov Decision Processes. AAAI/IAAI 2002: 285-291

Pascal Poupart, Craig Boutilier, Relu Patrascu, Dale Schuurmans: Piecewise Linear Value Function Approximation for Factored MDPs. AAAI/IAAI 2002: 292-299

Pascal Poupart, Craig Boutilier: Value-Directed Compression of POMDPs. NIPS 2002: 1547-1554

Pascal Poupart, Craig Boutilier: Vector-space Analysis of Belief-state Approximation for POMDPs. UAI 2001: 445-452

Pascal Poupart, Luis E. Ortiz, Craig Boutilier: Value-Directed Sampling Methods for POMDPs. UAI 2001: 453-461

Pascal Poupart, Craig Boutilier: Value-Directed Belief State Approximation for POMDPs. UAI 2000: 497-506