Publications (reversed chronological
order)
2018
- Order-Planning Neural Text Generation from Structured
Data
Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li,
Baobao Chang, Zhifang Sui,
Association for the Advancement of Artificial Intelligence
(AAAI), 8 pages, New Orleans, Louisiana, 2018.
[paper.pdf]
2017
- Deep Active Learning for Dialogue Generation
Nabiha Asghar, Pascal Poupart, Xin Jiang and Hang Li
Joint Conference on Lexical and Computational Semantics
(*SEM), 6 pages, Vancouver, BC, Canada, 2017
[paper.pdf]
- An Empirical Study of Branching Heuristics through the Lens
of Global Learning Rate
Jia Hui Liang, Hari Govind, Vijay Ganesh, Pascal Poupart,
Krzysztof Czarnecki
International Conference on Theory and applications of
Satisfiability Testing (SAT), 16 pages, Melbourne,
Australia, 2017. (runner up best student paper award)
[link]
- A Propagation Rate based Splitting Heuristic for
Divide-and-Conquer Solvers
Saeed Nejati, Zack Newsham, Joseph Scott, Jia Hui Liang,
Catherine Gebotys, Pascal Poupart and Vijay Ganesh
International Conference on Theory and applications of
Satisfiability Testing (SAT), 10 pages, Melbourne,
Australia, 2017.
[link]
- Constrained Bayesian Reinforcement Learning via Approximate
Linear Programming
Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim,
International Joint Conferences on Artificial Intelligence
(IJCAI), 8 pages, Sydney, Australia, 2017.
[paper.pdf]
- Online Bayesian Transfer Learning for Sequential Data
modeling
Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura
Middleton, Kayla Regan, Mike Schaekermann, George Trimponias,
James Tung, Pascal Poupart
International Conference on Learning Representations (ICLR),
20 pages, Toulon, France, 2017.
[paper.pdf]
- Online structure learning for sum-product networks with
Gaussian leaves
Wilson Hsu, Agastya Kalra, Pascal Poupart
International Conference on Learning Representations (ICLR) -
workshop track, 16 pages, Toulon, France, 2017.
[paper.pdf][code]
- Generative Mixture of Networks
Ershad Banijamali, Ali Ghodsi and Pascal Poupart
International Joint Conference on Neural Networks (IJCNN),
8 pages, Anchorage, Alaska, USA, 2017
[paper.pdf]
- Discovering Conversational Dependencies between Messages in
Dialogs
Wenchao Du, Pascal Poupart, Wei Xu
AAAI Student Abstract, 2 pages, San Francisco, CA, USA,
2017
[paper.pdf]
2016
- A Unified Approach for Learning the Parameters of
Sum-Product Networks
Han Zhao, Pascal Poupart and Geoff Gordon
Advances in Neural Information Processing Systems (NIPS),
9 pages, Barcelona, Spain, 2016.
[paper.pdf][supplement]
- Online Bayesian Moment Matching for Topic Modeling with
Unknown Number of Topics
Wei-Shou Hsu and Pascal Poupart
Advances in Neural Information Processing Systems (NIPS),
9 pages, Barcelona, Spain, 2016.
[paper.pdf][supplement][code]
- Dynamic Sum-Product Networks for Tractable Inference on
Sequence Data
Mazen Melibari, Pascal Poupart, Prashant Doshi, George
Trimponias
International Conference on Probabilistic Graphical Models
(PGM), 12 pages, Lugano, Switzerland, 2016.
[paper.pdf]
- Online Algorithms for Sum-Product Networks with Continuous
Variables
Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad
Banijamali, Zhitang Chen and Pascal Poupart
International Conference on Probabilistic Graphical Models
(PGM), 12 pages, Lugano, Switzerland, 2016.
[paper.pdf][code]
- Sum-Product-Max Networks for Tractable Decision Making
Mazen Melibari, Pascal Poupart and Prashant Doshi
International Joint Conference on Artificial Intelligence
(IJCAI), 7 pages, New York, USA, 2016
[paper.pdf]
- Learning Rate Based Branching Heuristic for SAT Solvers
Jia Hui Liang, Vijay Ganesh, Pascal Poupart and Krzysztof
Czarnecki
International Conference on Theory and Applications of
Satisfiability Testing (SAT), 17 pages, Bordeaux, France,
2016.
[paper.pdf]
- Online Relative Entropy Policy Search using Reproducing
Kernel Hilbert Space Embeddings
Zhitang Chen, Pascal Poupart and Yanhui Geng
International Conference on Artificial Intelligence and
Statistics (AISTATS), 9 pages, Cadiz, Spain, 2016.
[paper.pdf]
- Online and Distributed Bayesian Moment Matching for SPNs
Abdullah Rashwan, Han Zhao and Pascal Poupart
International Conference on Artificial Intelligence and
Statistics (AISTATS), 9 pages, Cadiz, Spain, 2016.
[paper.pdf]
- Exponential Recency Weighted Average Branching Heuristic
for SAT Solvers
Jia Hui Liang, Vijay Ganesh, Pascal Poupart and Krysztof
Czarnecki
Association for the Advancement of Artificial Intelligence
(AAAI), 7 pages, Phoenix, Arizona, 2016.
[paper.pdf]
2015
- On the Relationship Between Sum-Product Networks and
Bayesian Networks
Han Zhao, Mazen Meliberi, Pascal Poupart
International Conference on Machine Learning (ICML), 9
pages, Lille, France, 2015.
[paper.pdf][supplement][longer
arXiv version]
- Self-Adaptive Hierarchical Sentence Model
Han Zhao, Zhengdong Lu and Pascal Poupart,
International Joint Conference on Artificial Intelligence
(IJCAI), 8 pages, Buenos Aires, Argentina, 2015.
[paper.pdf]
- Incremental Policy Iteration with Guaranteed Escape from
Local Optima in POMDP Planning
Marek Grzes and Pascal Poupart
International Conference on Autonomous Agents and Multiagent
Systems (AAMAS), 9 pages, Istanbul, Turkey, 2015.
[paper.pdf]
- Energy Efficient Execution of POMDP Policies
Marek Grzes, Pascal Poupart, Xiao Yang and Jesse Hoey
IEEE Transactions on Systems Man and Cybernetics, Volume
45, Issue 11, pages 2484-2497, 2015
[link]
- SoF: Soft-Cluster Matrix Factorization for Probabilistic
Clustering
Han Zhao, Pascal Poupart, Yongfeng Zhang and Martin Lysy
Association for the Advancement of Artificial Intelligence
(AAAI), 8 pages, Austin, Texas, USA, 2015.
[paper.pdf]
- Approximate Linear Programming for Constrained Partially
Observable Markov Decision Processes
Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim,
Bongseok Goh and Michael Bowling
Association for the Advancement of Artificial Intelligence
(AAAI), 7 pages, Austin, Texas, USA, 2015.
[paper.pdf]
2014
- POMDP Planning and Execution in an Augmented Space
Marek Grzes and Pascal Poupart
International Conference on Autonomous Agents and Multiagent
Systems (AAMAS), 8 pages, Paris, France, 2014.
[paper.pdf]
- POMDP Planning by Marginal-MAP Probabilistic Inference in
Generative Models
Igor Kiselev and Pascal Poupart
AAMAS Workshop on Adaptive Learning Agents, 8 pages,
Paris, France, 2014.
[workshop
paper][extended
abstract]
- A Sober Look at Spectral Learning
Han Zhao and Pascal Poupart
ICML Workshop on the Method of Moments and Spectral Learning,
5 pages, Beijing, China, 2014.
[paper.pdf][code]
- Upper Limb Contributions to Frontal Plane Balance Control
in Rollator-Assisted Walking
James Y Tung, William H Gage, Pascal Poupart and William E
McIlroy
Assistive Technology, Volume 26, Issue 1, pages 15-21,
2014.
[link]
- Measuring life space in older adults with mild-to-moderate
Alzheimer's disease using mobile phone GPS
James Y Tung, Rhiannon V. Rose, Emnet Gammada, Isabel Lam,
Eric A. Roy, Sandra E. Black, Pascal Poupart
Gerontology, Volume 60, Issue 2, pages 154-162, 2014.
[link]
- Transparent Muscle Characterization Using Quantitative
Electromyography: Different Binarization Mappings
Meena AbdelMaseeh, T. Chen, Pascal Poupart, Ben Smith,
Daniel Stashuk
IEEE Transactions on Neural Systems and Rehabilitation
Engineering, Volume 22, Issue 3, pages 511-521, 2014
[link]
2013
- Controller Compilation and Compression for Resource
Constrained Applications
Marek Grzes, Pascal Poupart and Jesse Hoey
Algorithmic Decision Theory (ADT), 15 pages, Brussels,
Belgium, 2013.
[paper.pdf]
- Isomorph-free Branch and Bound Search for Finite State
Controllers
Marek Grzes, Pascal Poupart and Jesse Hoey
International Joint Conferences on Artificial Intelligence
(IJCAI), 7 pages, Beijing, China, 2013.
[paper.pdf]
- Learning Community-based Preferences via Dirichlet Process
Mixtures of Gaussian Processes
Ehsan Abbasnejad, Scott Sanner, Edwin V Bonilla and Pascal
Poupart
International Joint Conferences on Artificial Intelligence
(IJCAI), 7 pages, Beijing, China, 2013.
[paper.pdf][code]
- Iterative Model Refinement of Recommender MDPs based on
Expert Feedback
Omar Zia Khan, Pascal Poupart and John Mark Agosta
European Conference on Machine Learning and Principles and
Practice of Knowledge Discovery in Databases (ECMLPKDD),
16 pages, Prague, Czech Republic, 2013.
[paper.pdf]
2012
- People, Sensors, Decisions: Customizable and Adaptive
Technologies for Assistance in Healthcare
Jesse Hoey, Craig Boutilier, Pascal Poupart, Patrick Olivier,
Andrew Monk and Alex Mihailidis
ACM Transactions on Interactive Intelligent Systems,
Volume 2, Issue 4, 36 pages, 2012.
[link]
- Bayesian Reinforcement Learning
Nikos Vlassis, Mohammad Ghavamzadeh, Shie Mannor and Pascal
Poupart
Reinforcement Learning: State-of-the-Art, Springer
Verlag, Editors: Marco Wieiring and Martijn van Otterlo, pages
359-386, 2012
[link]
- Symbolic Dynamic Programming
for Continuous State and Observation POMDPs
Zhara Zamani, Scott Sanner, Pascal Poupart and Kristian Kersting
Neural Information Processing
Systems (NIPS), Lake Tahoe, NV, 2012.
[paper.pdf]
- Cost-Sensitive Exploration in
Bayesian Reinforcement Learning
Dongho Kim, Kee-Eung Kim and Pascal Poupart
Neural Information Processing
Systems (NIPS), Lake Tahoe, NV, 2012.
[paper.pdf]
- Hierarchical Double Dirichlet
Process Mixture of Gaussian Processes
Adita Tayal, Pascal Poupart and Yuying Li
National Conference on
Artificial Intelligence (AAAI), Toronto, ON, 2012.
[paper.pdf]
- Muscle Categorization using
Quantitative Needle Electromiography: A Two Stage Gaussian
Mixture Model based Approach
Meena Abdel Maseeh, Pascal Poupart, Benn Smith, Daniel Stashuk
International Conference on
Machine Learning Applications (ICMLA), Boca Raton, FL,
2012.
[paper.pdf]
2011
- An Introduction to Fully and
Partially Observable Markov Decision Processes
Pascal Poupart
Chapter 3 in Decision Theory
Models for Applications in Artificial Intelligence: Concepts
and Solutions, Eds. Enrique Sucar, Eduardo Morales and
Jesse Hoey, IGI Global, pages 33-62, 2011.
[link to book]
- POMDP Models for Assistive
Technology
Jesse Hoey, Pascal Poupart, Craig Boutilier and Alex Mihailidis
Chapter 13 in Decision Theory
Models for Applications in Artificial Intelligence: Concepts
and Solutions, Eds. Enrique Sucar, Eduardo Morales and
Jesse Hoey, IGI Global, pages 294-314, 2011.
[link to book]
- Automatically Generated
Explanations for Markov Decision Processes
Omar Zia Khan, Pascal Poupart and James Black
Chapter 7 in Decision Theory
Models for Applications in Artificial Intelligence: Concepts
and Solutions, Eds. Enrique Sucar, Eduardo Morales and
Jesse Hoey, IGI Global, pages 144-163, 2011.
[link to book]
- Automated Explanations for
MDP Policies
Omar Zia Khan, Pascal Poupart and James Black
NIPS Workshop on Decision
Making with Multiple Imperfect Decision Makers, Sierra
Nevada, Spain, 2011.
[paper.pdf]
(NB: This is a short paper that summarizes our ICAPS 2009 paper
as well as the book chapter above)
- Exploiting Structure in
Weighted Model Counting Approaches to Probabilistic Inference
Wei Li, Pascal Poupart and Peter van Beek
Journal of Artificial
Intelligence Research (JAIR), Volume 40, pages 729-765,
2011.
[paper.pdf]
- Automated Refinement of Bayes
Networks' Parameters based on Test Ordering Constraints
Omar Zian Khan, Pascal Poupart and John Mark Agosta
Advances in Neural Information
Processing Systems (NIPS), Grenada, Spain, 2011
[paper.pdf]
- Point-based Value Iteration
for Constrained POMDPs
Dongho Kim, Jaesong Lee, Kee-Eung Kim and Pascal Poupart
International Joint Conference
on Artificial Intelligence (IJCAI), Barcelona, Spain,
2011.
[paper.pdf]
- Continuous Correlated Beta
Processes
Robby Goetschalckx, Pascal Poupart and Jesse Hoey
International Joint Conference
on Artificial Intelligence (IJCAI), Barcelona, Spain,
2011.
[paper.pdf]
- Analyzing and Escaping Local
Optima in Planning as Inference for Partially Observable
Domains
Pascal Poupart, Tobias Lang and Marc Toussaint
European Conference on Machine
Learning (ECML), Athens, Greece, 2011.
[paper.pdf]
- Escaping Local Optima in
POMDP Planning as Inference
Pascal Poupart, Tobias Lang and Marc Toussaint
International Conference on
Autonomous Agents and Multiagent Systems (AAMAS),
Taipei, Taiwan, 2011.
[extended-abstract.pdf]
(NB: this is an extended abstract of the ECML paper above)
- Smart Walkers! Enhancing the
Mobility of the Elderly
Mathieu Sinn and Pascal Poupart
International Conference on
Autonomous Agents and Multiagent Systems (AAMAS),
Taipei, Taiwan, 2011.
[extended-abstract.pdf]
- Error Bounds for Online
Predictions of Linear-Chain Conditional Random Fields:
Application to Activity Recognition for Users of Rolling
Walkers
Mathieu Sinn and Pascal Poupart
IEEE International Conference
on Machine Learning and Applications (ICMLA), Honolulu,
Haiwai, 2011.
[link to paper]
- Closing the Gap: Improved
Bounds on Optimal POMDP Solutions
Pascal Poupart, Kee-Eung Kim and Dongho Kim
International Conference on
Automated Planning and Scheduling (ICAPS), Freiburg,
Germany, 2011.
[paper.pdf] [software]
- 3D Pose Tracking of Walker
Users' Lower Limb with a Structured Light Camera on a Moving
Platform
Richard Hu, Adam Hartfiel, James Tung, Adel Fakih, Jesse Hoey
and Pascal Poupart
Workshop on Human Activity
Understanding from 3D Data (HAU3D) at the IEEE Conference on
Computer Vision and Pattern Recognition (CVPR),
Colorado Springs, CO, 2011.
[paper.pdf]
- Asymptotic Theory for
Linear-Chain Conditional Random Fields
Mathieu Sinn and Pascal Poupart
International Conference on
Artificial Intelligence and Statistics (AISTATS), Fort
Lauderdale, FL, 2011
[paper.pdf][supplementary
material]
- A Bayesian Approach to Online
Performance Modeling for Database Appliances using Gaussian
Models
Muhammad Bilal Sheikh, Umar Farooq Minhas, Omar Zia Khan, Ashraf
Aboulnaga, Pascal Poupart and David J. Taylor
IEEE/ACM International
Conference on Autonomic Computing (ICAC), Karlsruhe,
Germany, 2011.
[paper.pdf]
- VALMA: Voice, Activity and
Location Monitoring for Alzheimer's Disease and Related
Dementias
James Y. Tung, Jonathan F.L. Semple, Wei Xian Woo, Wei-Shou Hsu,
Mathieu Sinn, Eric A. Roy and Pascal Poupart
Annual Conference of the
Rehabilitation Engineering and Assistive Technology Society of
North America (RESNA), Toronto, ON, 2011.
[paper.pdf]
- Ambulatory Assessment of
Lifestyle Factors for Alzheimer's Disease and Related
Dementias
James Y. Tung, Jonathan F. Semple, Wei Xian Woo, Wei-Shou Hsu,
Mathieu Sinn, Eric A. Roy and Pascal Poupart
AAAI Spring Symposium on
Computational Physiology, Stanford, CA, 2011.
[paper.pdf]
- Ambulatory Measurement of
Dual-Tasking Behaviour: Method and Preliminary Evaluation in
Older Adults
James Y. Tung, Eric A. Roy and Pascal Poupart
International Conference on
Ambulatory Monitoring of Physical Activity and Movement
(ICAMPAM), Glasgow, UK, 2011.
[paper.pdf]
2010
- Bayesian Reinforcement
Learning
Pascal Poupart
Encyclopedia of Machine
Learning, Editors: Claude Sammut and Geoffrey I. Webb,
Springer, pages 90-93, 2010.
[link to encyclopedia]
- Partially Observable Markov
Decision Processes
Pascal Poupart
Encyclopedia of Machine
Learning, Editors: Claude Sammut and Geoffrey I. Webb,
Springer, pages 754-760, 2010.
[link to encyclopedia]
- Comparative Analysis of
Probabilistic Models for Activity Recognition with an
Instrumented Walker
Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart,
James Tung and Allan Caine
Uncertainty in Artificial
Intelligence (UAI), Catalina, CA, 2010
[paper.pdf]
- Automated Handwashing
Assistance for Persons with Dementia Using Video and a
Partially Observable Markov Decision Process
Jesse Hoey, Pascal Poupart, Axel von Bertoldi, Tamy Craig, Craig
Boutilier and Alex Mihailidis
Computer Vision and Image
Understanding (CVIU), Volume 114, Issue 5, pages
503-519, May 2010.
[paper.pdf] [software]
- Evaluation Results for a
Query-Based Diagnostics Application
John Mark Agosta, Omar Zia Khan and Pascal Poupart
European Workshop on
Probabilistic Graphical Models (PGM), Helsinki,
Finland, 2010.
[paper.pdf]
- Activity Recognition for
Users of Rolling Walker Mobility Aids
Mathieu Sinn and Pascal Poupart
Workshop on Machine Learning
for Assistive Technologies at the International Conference on
Neural Information Processing Systems (NIPS), Whistler,
BC, 2010
[paper.pdf]
- Refining Diagnostic POMDPs
with User Feedback
Omar Zia Khan, Pascal Poupart and John-Mark Agosta
POMDP Practitioners Workshop:
Solving Real-World POMDP Problems at the International
Conference on Automated Planning and Scheduling (ICAPS),
Toronto, ON, 2010.
[paper.pdf]
- Automatic Speech Feature
Extraction for Cognitive Load Classification
Kiril Gorovoy, James Tung and Pascal Poupart
Conference of the Canadian
Medical and Biological Engineering Society (CMBEC),
Vancouver, BC, 2010
[paper.pdf]
2009
- Minimal Sufficient
Explanations for Factored Markov Decision Processes
Omar Zia Khan, Pascal Poupart and James Black
International Conference on
Automated Planning and Scheduling (ICAPS),
Thessaloniki, Greece, 2009.
[paper.pdf]
- Towards a Mobility Diagnostic
Tool: Tracking Rollator Users’ Leg Pose With a Monocular
Vision System
Samantha Ng, Adel Fakih, Adam Fourney, Pascal Poupart and John
Zelek
International Conference of
IEEE Engineering in Medicine and Biology Society (EMBC),
Minneapolis, 2009.
[paper.pdf]
- Probabilistic 3D Tracking:
Rollator User's Leg Pose from Coronal Images
Samantha Ng, Adel Fakih, Adam Fourney, Pascal Poupart and John
Zelek
Canadian Conference on
Computer and Robot Vision (CRV), Kelowna, BC, 2009.
[paper.pdf]
2008
- Partially Observable Markov
Decision Processes with Continuous Observations for Dialog
Management
Jason Williams, Pascal Poupart and Steve Young
Recent Trends in Discourse and
Dialogue, Editors L. Dybkjaer and W. Minker, Springer,
pages 191-217, 2008.
[paper.pdf]
- Towards Global Reinforcement
Learning
Milen Pavlov and Pascal Poupart,
NIPS Workshop on Model
Uncertainty and Risk in Reinforcement Learning,
Vancouver BC, 2008.
[paper.pdf]
- Explaining Recommendations
Generated by MDPs
Omar Zia Khan, Pascal Poupart and Jay Black,
ECAI Workshop on Explanation Aware Computing, Patras, Greece,
2008.
[paper.pdf]
- "Is the Sky Pure Today?"
AwkChecker an Assistive Tool for Detecting and Correcting
Collocation Errors
Taehyuen Park, Edward Lank, Pascal Poupart and Michael Terry
ACM Symposium on User
Interface Software and Technology (UIST), Monterrey,
California, 2008.
[paper.pdf]
- Efficient ADD Operations for
Point-Based Algorithms
Guy Shani, Ronen I. Brafman, Solomon E. Shimony and Pascal
Poupart
In Proceedings of the
Eighteenth International Conference on Automated Planning and
Scheduling (ICAPS), Sydney, Australia, 2008.
[paper.pdf]
- Hierarchical POMDP Controller
Optimization by Likelihood Maximization
Marc Toussaint, Laurent Charlin and Pascal Poupart
In Proceedings of the 24th
Conference on Uncertainty in Artificial Intelligence (UAI),
Helsinki, Finland, 2008.
[paper.pdf] best paper award runner up
- Exploiting Causal
Independence Using Weighted Model Counting
Wei Li, Pascal Poupart and Peter van Beek
In Proceedings of the 23rd
National Conference on Artificial Intelligence (AAAI),
Chicago, Illinois, 2008.
[paper.pdf]
- Model-based Bayesian
Reinforcement Learning in Partially Observable Domains
Pascal Poupart and Nikos Vlassis
International Symposium on
Artificial Intelligence and Mathematics (ISAIM), Fort
Lauderdale, Florida, 2008.
[paper.pdf]
2007
- Generating Lexical Analogies
using Dependency Relations
Andy Chiu, Pascal Poupart and Chrysanne DiMarco
In Proceedings of the
International Conference on Empirical Methods in Natural
Language Processing (EMNLP), Prague, Czech Republic,
2007.
[paper.pdf]
- Assisting Persons with
Dementia during Handwashing Using a Partially Observable
Markov Decision Process
Jesse Hoey, Axel von Bertoldi, Pascal Poupart, and Alex
Mihailidis
In Proceedings of the
International Conference on Vision Systems (ICVS),
Biefeld, Germany, 2007.
[paper.pdf] [software] best paper
award
2006
- Point-Based Value Iteration
for Continuous POMDPs
Josep M. Porta, Nikos Vlassis, Matthijs T.J. Spaan and Pascal
Poupart
Journal of Machine Learning
Research, Volume 7, pages 2329-2367, November 2006.
[paper.pdf]
- Constraint-based Optimization
and Utility Elicitation using the Minimax Decision Criteria
Craig Boutilier, Relu Patrascu, Pascal Poupart and Dale
Schuurmans
Artificial Intelligence,
volume 170, numbers 8-9, pages 686-713, June 2006.
[paper.pdf]
- A Planning System Based on
Markov Decision Processes to Guide People with Dementia
through Activities of Daily Living
Jennifer Boger, Jesse Hoey, Pascal Poupart, Craig Boutilier,
Geoff Fernie and Alex Mihailidis
IEEE Transactions on
Information Technology and Biomedicine, volume 10,
issue 2, pages 323-333, April 2006
[paper pdf]
- Automated Hierarchy Discovery
for Planning in Partially Observable Environments
Laurent Charlin, Pascal Poupart and Romy Shioda
In Advances in Neural Information Processing Systems 19
(NIPS), Vancouver, BC, 2006.
[paper.ps]
[paper.ps.gz]
[paper.pdf]
- Bayesian Reputation Modeling
in E-Marketplaces Sensitive to Subjectivity, Deception and
Change
Kevin Regan, Pascal Poupart and Robin Cohen
In Proceedings of the 21st
National Conference on Artificial Intelligence (AAAI),
Boston, MA, USA, 2006.
[paper.pdf]
- Performing Incremental
Bayesian Inference by Dynamic Model Counting
Wei Li, Peter van Beek and Pascal Poupart
In Proceedings of the 21st
National Conference on Artificial Intelligence (AAAI),
Boston, MA, USA, 2006.
[paper.pdf]
- Compact, Convex Upper Bound
Iteration for Approximate POMDP Planning
Tao Wang, Pascal Poupart, Michael Bowling and Dale Schuurmans
In Proceedings of the 21st
National Conference on Artificial Intelligence (AAAI),
Boston, MA, USA, 2006.
[paper.pdf]
- An Analytic Solution to
Discrete Bayesian Reinforcement Learning
Pascal Poupart, Nikos Vlassis, Jesse Hoey and Kevin Regan
In Proceedings of the 23rd
International Conference on Machine Learning (ICML),
pages 697-704, Pittsburgh, Pennsylvania, USA, 2006.
[paper.ps] [paper.ps.gz] [paper.pdf] [presentation.pdf]
- Learning Lexical Semantic
Relations using Lexical Analogies
Andy Chiu, Pascal Poupart and Chrysanne DiMarco
Ontologies in Text Technology
Workshop, Osnabrueck, Germany, 2006
[paper
pdf]
2005
- The Advisor-POMDP: A
Principled Approach to Trust through Reputation in Electronic
Markets
Kevin Regan, Robin Cohen
and Pascal Poupart
In Proceedings of the Third
Annual Conference on Privacy, Security and Trust (PST),
pages 121-130, St. Andrews, New Brunswick, Canada, 2005
[paper pdf]
- A Decision-Theoretic Approach to Task Assistance for
Persons with Dementia
Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier,
Geoff Fernie, and Alex Mihailidis
In Proceedings of the International Joint Conference on
Artificial Intelligence (IJCAI), pages 1293-1299,
Edinburgh, Scotland, 2005
[paper ps] [paper ps.gz] [paper pdf] [software]
- Regret-based Utility Elicitation in Constraint-based
Decision Problems
Craig Boutilier, Relu Patrscu, Pascal Poupart and Dale
Schuurmans
In Proceedings of the International Joint Conference on
Artificial Intelligence (IJCAI), pages 929-934, Edinburgh,
Scotland, 2005
[paper ps]
[paper
ps.gz] [paper pdf]
- Solving POMDPs with Continuous or Large Discrete
Observation Spaces
Jesse Hoey and Pascal Poupart
In Proceedings of the International Joint Conference on
Artificial Intelligence (IJCAI), pages 1332-1338,
Edinburgh, Scotland, 2005
[paper ps] [paper ps.gz]
[paper pdf]
- POMDP Models for Assistive
Technology
Jesse Hoey, Pascal Poupart, Craig Boutilier and Alex Mihailidis
In Proceedings of the AAAI
Fall Symposium on Caring Machines: AI in Eldercare,
Stanford, CA, 2005
[paper pdf]
- Partially Observable Markov
Decision Processes with Continuous Observations for Dialogue
Management
Jason D. Williams, Pascal Poupart and Steve Young
In Proceedings of the 6th
SigDial Workshop on Discourse and Dialogue, Lisbon,
Portugal, 2005.
[paper
pdf]
- Factored Partially Observable
Markov Decision Processes for Dialogue Management
Jason D. Williams, Pascal Poupart and Steve Young
In Proceedings of the 4th
IJCAI Workshop on Knowledge and Reasoning in Practical Dialog
Systems, Edinburgh, Scotland, 2005
[paper
pdf]
- Semi-Supervised Learning of a
POMDP Model of Patient-Caregiver Interactions
Jesse Hoey, Pascal Poupart, Craig Boutilier and Alex
Mihailidis
In Proceedings of the IJCAI
Workshop "Modeling Others From Observations" (MOO '05),
Edingurgh, Scotland, 2005
[paper ps][paper ps.gz][paper pdf]
- Exploiting Structure to Efficiently
Solve Large Scale Partially Observable Markov Decision
Processes
Pascal Poupart
Ph.D. thesis, Department of Computer Science, University of
Toronto, Toronto, 2005
[thesis ps][thesis ps.gz][thesis pdf][software]
- Using Factored Partially Observable Markov Decision
Processes with Continuous Observations for Dialogue Management
Jason D. Williams, Pascal Poupart and Steve Young
Cambridge University Engineering Department Technical Report:
CUED/F-INFENG/TR.520, March 2005.
[techreport pdf]
2004
- VDCBPI: an Approximate Scalable Algorithm for Large Scale
POMDPs
Pascal Poupart and Craig Boutilier
In Advances in Neural Information Processing Systems 17
(NIPS), pages 1081-1088, Vancouver, BC, 2004
[paper ps] [paper ps.gz] [paper pdf]
2003
- Bounded Finite
State Controllers
Pascal Poupart and Craig Boutilier
In Advances in Neural Information Processing Systems 16 (NIPS),
Vancouver, BC, 2003
[paper ps] [paper
ps.gz] [paper pdf] [NIPS presentation html] [NIPS poster html]
- Constraint-based
Optimization with the Minimax Decision Criterion
Craig Boutilier, Relu Patrascu, Pascal Poupart and Dale Schuurmans
In Proceedings of the Ninth International Conference on
Principles and Practice of Constraint Programming (CP),
pages 168-182, Kinsale, Ireland, 2003
[paper ps] [paper ps.gz] [paper pdf]
- Using a POMDP Controller to Guide
Persons With Dementia Through Activities of Daily Living
Jennifer Boger, Goeff Fernie, Pascal Poupart and Alex Mihailidis
In the Adjunct Proceedings of the Fifth International
Conference on Ubiquitous Computing (UBICOMP), pages
219-220, Seattle, WA, 2003.
[abstract ps][abstract
ps.gz][abstract pdf]
2002
- Value-directed
Compression
of POMDPs
Pascal Poupart and Craig Boutilier
In Advances in Neural Information Processing Systems 15 (NIPS),
pages 1547-1554, Vancouver, BC, 2002
[paper ps] [paper ps.gz] [paper pdf] [NIPS poster html]
- Piecewise
Linear Value Function Approximation for Factored MDPs
Pascal Poupart, Craig Boutilier, Relu Patrascu and Dale Schuurmans
In Proceedings of the Eighteenth National Conference on
Artificial Intelligence (AAAI), pages 292-299, Edmonton, AB,
2002
[paper ps] [paper ps.gz] [paper pdf] [AAAI poster html]
- Greedy
linear value-approximation for factored Markov decision
processes
Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier
and Carlos Guestrin
In Proceedings of the Eighteenth National Conference on
Artificial Intelligence (AAAI), pages 285-291, Edmonton, AB,
2002
[paper ps] [paper ps.gz] [paper pdf]
2001
- Value-Directed
Sampling Methods for Monitoring POMDPs
Pascal Poupart, Louis E. Ortiz and Craig Boutilier
In Proceedings of the Seventeenth Conference on Uncertainty in
Artificial Intelligence (UAI), pages 453-461, Seattle, WA,
2001
[paper ps] [paper ps.gz] [paper pdf] [UAI presentation html]
- Vector-Space Analysis of Belief-State
Approximation for POMDPs
Pascal Poupart and Craig Boutilier
In Proceedings of the Seventeenth Conference on Uncertainty in
Artificial Intelligence (UAI), pages 445-452, Seattle, WA,
2001
[paper ps] [paper ps.gz] [paper pdf] [UAI poster html]
2000
- Value-Directed Belief State Approximation
for POMDPs
Pascal Poupart and Craig Boutilier
In Proceedings of the Sixteenth Conference on Uncertainty in
Artificial Intelligence (UAI), pages 497-506, Stanford, CA,
2000
[paper ps][paper
ps.gz][paper pdf][UAI poster html]
- Approximate Value-Directed Belief
State Monitoring for Partially Observable Markov Decision
Processes
Pascal Poupart
Master's thesis, Department of Computer Science, University of
British Columbia, Vancouver, 2000
[thesis ps][thesis ps.gz][thesis pdf]
Presentations (selected)
- A Smart
Walker to Understand Walking Abilities, U of Kentucky,
Lexington, 2010
- Explaining
Automated
Policies for Sequential Decision Making, Intel 2009, UBC
2009, U of Kentucky 2010.
- Symbolic
Perseus:
a Genetric POMDP Algorithm with Application from Dynamic
Pricing with Demand Learning, INFORMS, San Diego, 2009.
- Non-Myopic Active Learning: A Reinforcement
Learning Approach, Google, Waterloo, 2009
- Tutorial on
Bayesian Techniques for Reinforcement Learning,
International Conference on Machine Learning (ICML), June 2007.
- Towards
Bayesian Reinforcement Learning, NIPS workshop: Towards a
New Reinforcement Learning?, Dec 2006.
- Topics
of Active Research in Reinforcement Learning Relevant to
Spoken Dialogue Systems, AAAI workshop on Empirical
and Statistical Methods for Spoken Dialogue Systems, July 2006.