Pascal Poupart

255 papers A* 60A 33B 4C 1Misc 2Journal 107Unranked 42

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Practical Algorithm for Feature-Rich, Non-Stationary Bandit Problems. CoRR Wei Min Loh, Sajib Kumer Sinha, Ankur Agarwal, Pascal Poupart
2026	J	`jnl`	A Practical Algorithm for Feature-Rich, Non-Stationary Bandit Problems. Trans. Mach. Learn. Res. William Loh, Sajib Kumer Sinha, Ankur Agarwal, Pascal Poupart
2026	J	`jnl`	FedBNR: A Fully Global Federated Gaussian Process. Mach. Learn. Haolin Yu, Kaiyang Guo, Mahdi Karami, Guojun Zhang, Hongliang Li, Xi Chen, Pascal Poupart
2026	J	`jnl`	FedLog: Personalized Federated Classification with Less Communication and More Flexibility. Trans. Mach. Learn. Res. Haolin Yu, Guojun Zhang, Hongliang Li, Pascal Poupart
2026	J	`jnl`	Talk, Judge, Cooperate: Gossip-Driven Indirect Reciprocity in Self-Interested LLM Agents. CoRR Shuhui Zhu, Yue Lin, Shriya Kaistha, Wenhao Li, Baoxiang Wang, Hongyuan Zha, Gillian K. Hadfield, Pascal Poupart
2025	J	`jnl`	A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges. Trans. Mach. Learn. Res. Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart
2025	J	`jnl`	A Minimalist Method for Fine-tuning Text-to-Image Diffusion Models. CoRR Yanting Miao, William Loh, Pascal Poupart, Suraj Kothawade
2025	J	`jnl`	Basis Transformers for Multi-Task Tabular Regression. CoRR Wei Min Loh, Jiaqi Shang, Pascal Poupart
2025	J	`jnl`	Chrysalis: A Unified System for Comparing Active Teaching and Passive Learning with AI Agents in Education. CoRR Prashanth Arun, Vinita Vader, Erya Xu, Brent McCready-Branch, Sarah Seabrook, Kyle Scholz, Ana Crisan, Igor Grossmann, Pascal Poupart
2025	J	`jnl`	Image-POSER: Reflective RL for Multi-Expert Image Generation and Editing. CoRR Hossein Mohebbi, Mohammed Abdulrahman, Yanting Miao, Pascal Poupart, Suraj Kothawade
2025	J	`jnl`	Information Bargaining: Bilateral Commitment in Bayesian Persuasion. CoRR Yue Lin, Shuhui Zhu, William A. Cunningham, Wenhao Li, Pascal Poupart, Hongyuan Zha, Baoxiang Wang
2025	A	`conf`	Learning to Negotiate via Voluntary Commitment. AISTATS Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
2025	J	`jnl`	Learning to Negotiate via Voluntary Commitment. CoRR Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart
2025	J	`jnl`	Measures of Variability for Risk-averse Policy Gradient. CoRR Yudong Luo, Yangchen Pan, Jiaqi Tan, Pascal Poupart
2025	J	`jnl`	Policy-Conditioned Policies for Multi-Agent Task Solving. CoRR Yue Lin, Shuhui Zhu, Wenhao Li, Ang Li, Dan Qiao, Pascal Poupart, Hongyuan Zha, Baoxiang Wang
2025	A*	`conf`	Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens. ICML Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart
2025	J	`jnl`	Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens. CoRR Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart
2025	J	`jnl`	Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling. CoRR Gustavo Sutter, Mohammed Abdulrahman, Hao Wang, Sriram Ganapathi Subramanian, Marc St-Aubin, Sharon O'Sullivan, Lawrence Wan, Luis A. Ricardez-Sandoval, Pascal Poupart, Agustinus Kristiadi
2025	—	`conf`	Target Attribute Diffusion Models. ICCVW William Loh, Yanting Miao, Pascal Poupart, Suraj Kothawade
2025	J	`jnl`	Time Is Effort: Estimating Human Post-Editing Time for Grammar Error Correction Tool Evaluation. CoRR Ankit Vadehra, Bill Johnson, Gene Saunders, Pascal Poupart
2025	A*	`conf`	Towards Cost-Effective Reward Guided Text Generation. ICML Ahmad Rashid, Ruotian Wu, Rongqi Fan, Hongliang Li, Agustinus Kristiadi, Pascal Poupart
2025	J	`jnl`	Towards Cost-Effective Reward Guided Text Generation. CoRR Ahmad Rashid, Ruotian Wu, Rongqi Fan, Hongliang Li, Agustinus Kristiadi, Pascal Poupart
2025	A*	`conf`	Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning. ICLR Bo Yue, Shufan Wang, Ashish Gaurav, Jian Li, Pascal Poupart, Guiliang Liu
2025	J	`jnl`	When Should Reinforcement Learning Use Causal Reasoning? Trans. Mach. Learn. Res. Oliver Schulte, Pascal Poupart
2024	J	`jnl`	A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges. CoRR Guiliang Liu, Sheng Xu, Shicheng Liu, Ashish Gaurav, Sriram Ganapathi Subramanian, Pascal Poupart
2024	J	`jnl`	A Critical Look At Tokenwise Reward-Guided Text Generation. CoRR Ahmad Rashid, Ruotian Wu, Julia Grosse, Agustinus Kristiadi, Pascal Poupart
2024	J	`jnl`	A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization. RLJ Yudong Luo, Yangchen Pan, Han Wang, Philip Torr, Pascal Poupart
2024	J	`jnl`	A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization. CoRR Yudong Luo, Yangchen Pan, Han Wang, Philip Torr, Pascal Poupart
2024	A*	`conf`	A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? ICML Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alán Aspuru-Guzik, Geoff Pleiss
2024	J	`jnl`	A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? CoRR Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alán Aspuru-Guzik, Geoff Pleiss
2024	A*	`conf`	Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space. AAAI Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart
2024	A*	`conf`	Confidence Aware Inverse Constrained Reinforcement Learning. ICML Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
2024	J	`jnl`	Confidence Aware Inverse Constrained Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
2024	J	`jnl`	FedLog: Personalized Federated Classification with Less Communication and More Flexibility. CoRR Haolin Yu, Guojun Zhang, Pascal Poupart
2024	J	`jnl`	How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization? CoRR Agustinus Kristiadi, Felix Strieth-Kalthoff, Sriram Ganapathi Subramanian, Vincent Fortuin, Pascal Poupart, Geoff Pleiss
2024	J	`jnl`	Label Alignment Regularization for Distribution Shift. J. Mach. Learn. Res. Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip H. S. Torr, Yangchen Pan
2024	J	`jnl`	Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories. CoRR Niloufar Saeidi Mobarakeh, Behzad Khamidehi, Chunlin Li, Hamidreza Mirkhani, Fazel Arasteh, Mohammed Elmahgiubi, Weize Zhang, Kasra Rezaee, Pascal Poupart
2024	A	`conf`	Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks. AISTATS Ahmad Rashid, Serena Hacker, Guojun Zhang, Agustinus Kristiadi, Pascal Poupart
2024	A*	`conf`	Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning. NeurIPS Yanting Miao, William Loh, Suraj Kothawade, Pascal Poupart, Abdullah Rashwan, Yeqing Li
2024	J	`jnl`	Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning. CoRR Yanting Miao, William Loh, Suraj Kothawade, Pascal Poupart, Abdullah Rashwan, Yeqing Li
2024	J	`jnl`	Uncertainty-Guided Optimization on Large Language Model Search Trees. CoRR Julia Grosse, Ruotian Wu, Ahmad Rashid, Philipp Hennig, Pascal Poupart, Agustinus Kristiadi
2024	J	`jnl`	Why Online Reinforcement Learning is Causal. CoRR Oliver Schulte, Pascal Poupart
2023	A*	`conf`	An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. NeurIPS Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan
2023	J	`jnl`	An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient. CoRR Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan
2023	—	`conf`	Attribute Controlled Dialogue Prompting. ACL (Findings) Runcheng Liu, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart
2023	J	`jnl`	Attribute Controlled Dialogue Prompting. CoRR Runcheng Liu, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart
2023	A*	`conf`	Batchnorm Allows Unsupervised Radial Attacks. NeurIPS Amur Ghose, Apurv Gupta, Yaoliang Yu, Pascal Poupart
2023	A*	`conf`	Benchmarking Constraint Inference in Inverse Reinforcement Learning. ICLR Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart
2023	J	`jnl`	Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space. CoRR Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart
2023	—	`conf`	Contrastive Deterministic Autoencoders For Language Modeling. EMNLP (Findings) Amur Ghose, Pascal Poupart
2023	A	`conf`	Defensive Collaborative Learning: Protecting Objective Privacy in Data Sharing. AAMAS Cynthia Huang, Pascal Poupart
2023	A	`conf`	Do we need Label Regularization to Fine-tune Pre-trained Language Models? EACL Ivan Kobyzev, Aref Jafari, Mehdi Rezagholizadeh, Tianda Li, Alan Do-Omri, Peng Lu, Pascal Poupart, Ali Ghodsi
2023	A	`conf`	FedFormer: Contextual Federation with Attention in Reinforcement Learning. AAMAS Liam Hebert, Lukasz Golab, Pascal Poupart, Robin Cohen
2023	A*	`conf`	Learning Soft Constraints From Constrained Expert Demonstrations. ICLR Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart
2023	A*	`conf`	Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations. NeurIPS Guanren Qiao, Guiliang Liu, Pascal Poupart, Zhiqiang Xu
2023	A	`conf`	NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge. AISTATS Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart
2023	J	`jnl`	Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks. CoRR Ahmad Rashid, Serena Hacker, Guojun Zhang, Agustinus Kristiadi, Pascal Poupart
2022	J	`jnl`	Benchmarking Constraint Inference in Inverse Reinforcement Learning. CoRR Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart
2022	B	`conf`	CILDA: Contrastive Data Augmentation Using Intermediate Layer Knowledge Distillation. COLING Md. Akmal Haidar, Mehdi Rezagholizadeh, Abbas Ghaddar, Khalil Bibi, Philippe Langlais, Pascal Poupart
2022	J	`jnl`	CILDA: Contrastive Data Augmentation using Intermediate Layer Knowledge Distillation. CoRR Md. Akmal Haidar, Mehdi Rezagholizadeh, Abbas Ghaddar, Khalil Bibi, Philippe Langlais, Pascal Poupart
2022	—	`conf`	Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization. EMNLP (Findings) Aref Jafari, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart, Ali Ghodsi
2022	J	`jnl`	Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization. CoRR Aref Jafari, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart, Ali Ghodsi
2022	A*	`conf`	Decentralized Mean Field Games. AAAI Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2022	A*	`conf`	Distributional Reinforcement Learning with Monotonic Splines. ICLR Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart
2022	J	`jnl`	FedFormer: Contextual Federation with Attention in Reinforcement Learning. CoRR Liam Hebert, Lukasz Golab, Pascal Poupart, Robin Cohen
2022	J	`jnl`	Federated Bayesian Neural Regression: A Scalable Global Federated Gaussian Process. CoRR Haolin Yu, Kaiyang Guo, Mahdi Karami, Xi Chen, Guojun Zhang, Pascal Poupart
2022	J	`jnl`	Label Alignment Regularization for Distribution Shift. CoRR Ehsan Imani, Guojun Zhang, Jun Luo, Pascal Poupart, Yangchen Pan
2022	J	`jnl`	Learning Functions on Multiple Sets using Multi-Set Transformers. CoRR Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart
2022	A*	`conf`	Learning Object-Oriented Dynamics for Planning from Text. ICLR Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart
2022	J	`jnl`	Learning Soft Constraints From Constrained Expert Demonstrations. CoRR Ashish Gaurav, Kasra Rezaee, Guiliang Liu, Pascal Poupart
2022	A	`conf`	Learning functions on multiple sets using multi-set transformers. UAI Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart
2022	A	`conf`	Linearizing contextual bandits with latent state dynamics. UAI Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart
2022	J	`jnl`	Optimality and Stability in Non-Convex Smooth Games. J. Mach. Learn. Res. Guojun Zhang, Pascal Poupart, Yaoliang Yu
2022	—	`conf`	RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation. NAACL-HLT (Findings) Md. Akmal Haidar, Nithin Anchuri, Mehdi Rezagholizadeh, Abbas Ghaddar, Philippe Langlais, Pascal Poupart
2022	J	`jnl`	Robust One Round Federated Learning with Predictive Space Bayesian Inference. CoRR Mohsin Hasan, Zehao Zhang, Kaiyang Guo, Mahdi Karami, Guojun Zhang, Xi Chen, Pascal Poupart
2022	J	`jnl`	Towards Understanding Label Regularization for Fine-tuning Pre-trained Language Models. CoRR Ivan Kobyzev, Aref Jafari, Mehdi Rezagholizadeh, Tianda Li, Alan Do-Omri, Peng Lu, Ali Ghodsi, Pascal Poupart
2022	A*	`conf`	Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. NeurIPS Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart
2022	—	`conf`	WatClaimCheck: A new Dataset for Claim Entailment and Inference. ACL (1) Kashif Khan, Ruizhe Wang, Pascal Poupart
2021	J	`jnl`	Decentralized Mean Field Games. CoRR Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2021	A*	`conf`	Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning. NeurIPS Guiliang Liu, Xiangyu Sun, Oliver Schulte, Pascal Poupart
2021	J	`jnl`	NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge. CoRR Xiangyu Sun, Guiliang Liu, Pascal Poupart, Oliver Schulte
2021	A	`conf`	Partially Observable Mean Field Reinforcement Learning. AAMAS Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2021	J	`jnl`	Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks. CoRR Xiangle Cheng, James He, Shihan Xiao, Yingxue Zhang, Zhitang Chen, Pascal Poupart, Fenglin Li
2021	A*	`conf`	Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning. ICCV Ershad Banijamali, Mohsen Rohani, Elmira Amirloo Abolfathi, Jun Luo, Pascal Poupart
2021	A*	`conf`	Quantifying and Improving Transferability in Domain Generalization. NeurIPS Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart
2021	J	`jnl`	Quantifying and Improving Transferability in Domain Generalization. CoRR Guojun Zhang, Han Zhao, Yaoliang Yu, Pascal Poupart
2021	J	`jnl`	RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation. CoRR Md. Akmal Haidar, Nithin Anchuri, Mehdi Rezagholizadeh, Abbas Ghaddar, Philippe Langlais, Pascal Poupart
2021	J	`jnl`	Robust Embeddings Via Distributions. CoRR Kira A. Selby, Yinong Wang, Ruizhe Wang, Peyman Passban, Ahmad Rashid, Mehdi Rezagholizadeh, Pascal Poupart
2021	A*	`conf`	Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map. CVPR Elmira Amirloo Abolfathi, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart
2021	J	`jnl`	Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map. CoRR Elmira Amirloo Abolfathi, Mohsen Rohani, Ershad Banijamali, Jun Luo, Pascal Poupart
2020	A	`conf`	Batch norm with entropic regularization turns deterministic autoencoders into generative models. UAI Amur Ghose, Abdullah Rashwan, Pascal Poupart
2020	J	`jnl`	Batch norm with entropic regularization turns deterministic autoencoders into generative models. CoRR Amur Ghose, Abdullah Rashwan, Pascal Poupart
2020	J	`jnl`	Complete Hierarchy of Relaxation for Constrained Signomial Positivity. CoRR Allen Houze Wang, Priyank Jaini, Yaoliang Yu, Pascal Poupart
2020	A*	`conf`	Diachronic Embedding for Temporal Knowledge Graph Completion. AAAI Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart
2020	J	`jnl`	Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch. Int. J. Approx. Reason. Haonan Duan, Abdullah Rashwan, Pascal Poupart, Zhitang Chen
2020	J	`jnl`	Generating Emotionally Aligned Responses in Dialogues using Affect Control Theory. CoRR Nabiha Asghar, Ivan Kobyzev, Jesse Hoey, Pascal Poupart, Muhammad Bilal Sheikh
2020	A*	`conf`	Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players. IJCAI Yudong Luo, Oliver Schulte, Pascal Poupart
2020	A*	`conf`	Learning Agent Representations for Ice Hockey. NeurIPS Guiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan
2020	A*	`conf`	Learning Dynamic Belief Graphs to Generalize on Text-Based Games. NeurIPS Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
2020	J	`jnl`	Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games. CoRR Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
2020	J	`jnl`	Learning directed acyclic graph SPNs in sub-quadratic time. Int. J. Approx. Reason. Amur Ghose, Priyank Jaini, Pascal Poupart
2020	J	`jnl`	MatrixNets: A New Scale and Aspect Ratio Aware Architecture for Object Detection. CoRR Abdullah Rashwan, Rishav Agarwal, Agastya Kalra, Pascal Poupart
2020	A	`conf`	Multi Type Mean Field Reinforcement Learning. AAMAS Sriram Ganapathi Subramanian, Pascal Poupart, Matthew E. Taylor, Nidhi Hegde
2020	J	`jnl`	Multi Type Mean Field Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Pascal Poupart, Matthew E. Taylor, Nidhi Hegde
2020	J	`jnl`	Newton-type Methods for Minimax Optimization. CoRR Guojun Zhang, Kaiwen Wu, Pascal Poupart, Yaoliang Yu
2020	A*	`conf`	Online Bayesian Moment Matching based SAT Solver Heuristics. ICML Haonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh
2020	J	`jnl`	Optimality and Stability in Non-Convex-Non-Concave Min-Max Optimization. CoRR Guojun Zhang, Pascal Poupart, Yaoliang Yu
2020	J	`jnl`	Partially Observable Mean Field Reinforcement Learning. CoRR Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley, Pascal Poupart
2020	J	`jnl`	Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning. CoRR Ershad Banijamali, Mohsen Rohani, Elmira Amirloo Abolfathi, Jun Luo, Pascal Poupart
2020	A*	`conf`	Progressive Memory Banks for Incremental Domain Adaptation. ICLR Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang
2020	J	`jnl`	Representation Learning for Dynamic Graphs: A Survey. J. Mach. Learn. Res. Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart
2020	A*	`conf`	Unsupervised Multilingual Alignment using Wasserstein Barycenter. IJCAI Xin Lian, Kshitij Jain, Jakub Truszkowski, Pascal Poupart, Yaoliang Yu
2020	J	`jnl`	Unsupervised Multilingual Alignment using Wasserstein Barycenter. CoRR Xin Lian, Kshitij Jain, Jakub Truszkowski, Pascal Poupart, Yaoliang Yu
2019	A	`conf`	Comparing EM with GD in Mixture Models of Two Components. UAI Guojun Zhang, Pascal Poupart, George Trimponias
2019	J	`jnl`	Comparing EM with GD in Mixture Models of Two Components. CoRR Guojun Zhang, Pascal Poupart, George Trimponias
2019	J	`jnl`	Diachronic Embedding for Temporal Knowledge Graph Completion. CoRR Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Pascal Poupart
2019	—	`conf`	Matrix Nets: A New Deep Architecture for Object Detection. ICCV Workshops Abdullah Rashwan, Agastya Kalra, Pascal Poupart
2019	J	`jnl`	Matrix Nets: A New Deep Architecture for Object Detection. CoRR Abdullah Rashwan, Agastya Kalra, Pascal Poupart
2019	A	`conf`	On the Relationship Between Satisfiability and Markov Decision Processes. UAI Ricardo Salmon, Pascal Poupart
2019	J	`jnl`	Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey. CoRR Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart
2019	J	`jnl`	SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting
2019	J	`jnl`	Time2Vec: Learning a Vector Representation of Time. CoRR Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, Marcus A. Brubaker
2019	Misc	`conf`	Why Do Neural Dialog Systems Generate Short and Meaningless Replies? a Comparison between Dialog and Translation. ICASSP Bolin Wei, Shuai Lu, Lili Mou, Hao Zhou, Pascal Poupart, Ge Li, Zhi Jin
2018	A	`conf`	Affective Neural Response Generation. ECIR Nabiha Asghar, Pascal Poupart, Jesse Hoey, Xin Jiang, Lili Mou
2018	A*	`conf`	An Empirical Study of Branching Heuristics through the Lens of Global Learning Rate. IJCAI Jia Liang, Hari Govind V. K., Pascal Poupart, Krzysztof Czarnecki, Vijay Ganesh
2018	—	`conf`	An Empirical Study of Methods for SPN Learning and Inference. PGM Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, André L. Teixeira, Pascal Poupart, Agastya Kalra
2018	A*	`conf`	Deep Homogeneous Mixture Models: Representation, Separation, and Approximation. NeurIPS Priyank Jaini, Pascal Poupart, Yaoliang Yu
2018	—	`conf`	Discriminative Training of Sum-Product Networks by Extended Baum-Welch. PGM Abdullah Rashwan, Pascal Poupart, Zhitang Chen
2018	A	`conf`	Faster Policy Adaptation in Environments with Exogeneity: A State Augmentation Approach. AAMAS Zhuoshu Li, Zhitang Chen, Pascal Poupart, Sanmay Das, Yanhui Geng
2018	A*	`conf`	Monte-Carlo Tree Search for Constrained POMDPs. NeurIPS Jongmin Lee, Geon-Hyeong Kim, Pascal Poupart, Kee-Eung Kim
2018	A*	`conf`	Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks. NeurIPS Agastya Kalra, Abdullah Rashwan, Wei-Shou Hsu, Pascal Poupart, Prashant Doshi, Georgios Trimponias
2018	A*	`conf`	Order-Planning Neural Text Generation From Structured Data. AAAI Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, Zhifang Sui
2018	J	`jnl`	Progressive Memory Banks for Incremental Domain Adaptation. CoRR Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang
2018	—	`conf`	Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks. PGM Priyank Jaini, Amur Ghose, Pascal Poupart
2018	A*	`conf`	Unsupervised Video Object Segmentation for Deep Reinforcement Learning. NeurIPS Vikash Goel, Jameson Weng, Pascal Poupart
2018	J	`jnl`	Unsupervised Video Object Segmentation for Deep Reinforcement Learning. CoRR Vik Goel, Jameson Weng, Pascal Poupart
2018	B	`conf`	Variational Attention for Sequence-to-Sequence Models. COLING Hareesh Bahuleyan, Lili Mou, Olga Vechtomova, Pascal Poupart
2017	A	`conf`	A Propagation Rate Based Splitting Heuristic for Divide-and-Conquer Solvers. SAT Saeed Nejati, Zack Newsham, Joseph Scott, Jia Hui Liang, Catherine H. Gebotys, Pascal Poupart, Vijay Ganesh
2017	J	`jnl`	Affective Neural Response Generation. CoRR Nabiha Asghar, Pascal Poupart, Jesse Hoey, Xin Jiang, Lili Mou
2017	A	`conf`	An Empirical Study of Branching Heuristics Through the Lens of Global Learning Rate. SAT Jia Hui Liang, Hari Govind V. K., Pascal Poupart, Krzysztof Czarnecki, Vijay Ganesh
2017	—	`ch.`	Bayesian Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining Pascal Poupart
2017	A*	`conf`	Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. IJCAI Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim
2017	—	`conf`	Deep Active Learning for Dialogue Generation. *SEM Nabiha Asghar, Pascal Poupart, Xin Jiang, Hang Li
2017	A*	`conf`	Discovering Conversational Dependencies between Messages in Dialogs. AAAI Wenchao Du, Pascal Poupart, Wei Xu
2017	J	`jnl`	Generative Mixture of Networks. CoRR Ershad Banijamali, Ali Ghodsi, Pascal Poupart
2017	B	`conf`	Generative mixture of networks. IJCNN Ershad Banijamali, Ali Ghodsi, Pascal Poupart
2017	J	`jnl`	On Improving Deep Reinforcement Learning for POMDPs. CoRR Pengfei Zhu, Xin Li, Pascal Poupart
2017	—	`conf`	Online Bayesian Transfer Learning for Sequential Data Modeling. ICLR (Poster) Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart
2017	—	`conf`	Online Structure Learning for Sum-Product Networks with Gaussian Leaves. ICLR (Workshop) Wilson Hsu, Agastya Kalra, Pascal Poupart
2017	J	`jnl`	Online Structure Learning for Sum-Product Networks with Gaussian Leaves. CoRR Wilson Hsu, Agastya Kalra, Pascal Poupart
2017	J	`jnl`	Order-Planning Neural Text Generation From Structured Data. CoRR Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, Zhifang Sui
2017	—	`ch.`	Partially Observable Markov Decision Processes. Encyclopedia of Machine Learning and Data Mining Pascal Poupart
2017	J	`jnl`	Variational Attention for Sequence-to-Sequence Models. CoRR Hareesh Bahuleyan, Lili Mou, Olga Vechtomova, Pascal Poupart
2017	J	`jnl`	Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation. CoRR Bolin Wei, Shuai Lu, Lili Mou, Hao Zhou, Pascal Poupart, Ge Li, Zhi Jin
2016	—	`conf`	A Unified Approach for Learning the Parameters of Sum-Product Networks. NIPS Han Zhao, Pascal Poupart, Geoffrey J. Gordon
2016	J	`jnl`	A Unified Approach for Learning the Parameters of Sum-Product Networks. CoRR Han Zhao, Pascal Poupart, Geoffrey J. Gordon
2016	A*	`conf`	Decision Sum-Product-Max Networks. AAAI Mazen Melibari, Pascal Poupart, Prashant Doshi
2016	J	`jnl`	Discovering Conversational Dependencies between Messages in Dialogs. CoRR Wenchao Du, Pascal Poupart, Wei Xu
2016	—	`conf`	Dynamic Sum Product Networks for Tractable Inference on Sequence Data. Probabilistic Graphical Models Mazen Melibari, Pascal Poupart, Prashant Doshi, George Trimponias
2016	A*	`conf`	Exponential Recency Weighted Average Branching Heuristic for SAT Solvers. AAAI Jia Hui Liang, Vijay Ganesh, Pascal Poupart, Krzysztof Czarnecki
2016	A	`conf`	Learning Rate Based Branching Heuristic for SAT Solvers. SAT Jia Hui Liang, Vijay Ganesh, Pascal Poupart, Krzysztof Czarnecki
2016	—	`conf`	Online Algorithms for Sum-Product Networks with Continuous Variables. Probabilistic Graphical Models Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart
2016	—	`conf`	Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics. NIPS Wei-Shou Hsu, Pascal Poupart
2016	A	`conf`	Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings. AISTATS Zhitang Chen, Pascal Poupart, Yanhui Geng
2016	J	`jnl`	Online Sequence-to-Sequence Active Learning for Open-Domain Dialogue Generation. CoRR Nabiha Asghar, Pascal Poupart, Xin Jiang, Hang Li
2016	A	`conf`	Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks. AISTATS Abdullah Rashwan, Han Zhao, Pascal Poupart
2016	J	`jnl`	Online and Distributed learning of Gaussian mixture models by Bayesian Moment Matching. CoRR Priyank Jaini, Pascal Poupart
2016	B	`conf`	Online flow size prediction for improved network routing. ICNP Pascal Poupart, Zhitang Chen, Priyank Jaini, Fred Fung, Hengky Susanto, Yanhui Geng, Li Chen, Kai Chen, Hao Jin
2016	—	`conf`	Overfitting at SemEval-2016 Task 3: Detecting Semantically Similar Questions in Community Question Answering Forums with Word Embeddings. SemEval@NAACL-HLT Hujie Wang, Pascal Poupart
2016	A*	`conf`	Sum-Product-Max Networks for Tractable Decision Making. IJCAI Mazen Melibari, Pascal Poupart, Prashant Doshi
2016	A	`conf`	Sum-Product-Max Networks for Tractable Decision Making: (Extended Abstract). AAMAS Mazen A. Melibari, Pascal Poupart, Prashant Doshi
2015	A*	`conf`	Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. AAAI Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling
2015	J	`jnl`	Dynamic Sum Product Networks for Tractable Inference on Sequence Data. CoRR Mazen Melibari, Pascal Poupart, Prashant Doshi
2015	J	`jnl`	Energy Efficient Execution of POMDP Policies. IEEE Trans. Cybern. Marek Grzes, Pascal Poupart, Xiao Yang, Jesse Hoey
2015	A	`conf`	Incremental Policy Iteration with Guaranteed Escape from Local Optima in POMDP Planning. AAMAS Marek Grzes, Pascal Poupart
2015	A*	`conf`	On the Relationship between Sum-Product Networks and Bayesian Networks. ICML Han Zhao, Mazen Melibari, Pascal Poupart
2015	J	`jnl`	On the Relationship between Sum-Product Networks and Bayesian Networks. CoRR Han Zhao, Mazen Melibari, Pascal Poupart
2015	A*	`conf`	Self-Adaptive Hierarchical Sentence Model. IJCAI Han Zhao, Zhengdong Lu, Pascal Poupart
2015	J	`jnl`	Self-Adaptive Hierarchical Sentence Model. CoRR Han Zhao, Zhengdong Lu, Pascal Poupart
2015	A*	`conf`	SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering. AAAI Han Zhao, Pascal Poupart, Yongfeng Zhang, Martin Lysy
2015	—	`conf`	Think fast - resource constrained reasoning and planning under uncertainty. TAAI Pascal Poupart
2014	A*	`conf`	A Novel Single-DBN Generative Model for Optimizing POMDP Controllers by Probabilistic Inference. AAAI Igor Kiselev, Pascal Poupart
2014	J	`jnl`	A Sober Look at Spectral Learning. CoRR Han Zhao, Pascal Poupart
2014	J	`jnl`	Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference. CoRR Wei Li, Pascal Poupart, Peter van Beek
2014	A	`conf`	POMDP planning and execution in an augmented space. AAMAS Marek Grzes, Pascal Poupart
2014	A	`conf`	Policy optimization by marginal-map probabilistic inference in generative models. AAMAS Igor Kiselev, Pascal Poupart
2013	—	`conf`	Controller Compilation and Compression for Resource Constrained Applications. ADT Marek Grzes, Pascal Poupart, Jesse Hoey
2013	A*	`conf`	Isomorph-Free Branch and Bound Search for Finite State Controllers. IJCAI Marek Grzes, Pascal Poupart, Jesse Hoey
2013	—	`conf`	Iterative Model Refinement of Recommender MDPs Based on Expert Feedback. ECML/PKDD (1) Omar Zia Khan, Pascal Poupart, John Mark Agosta
2013	A*	`conf`	Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes. IJCAI Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart
2013	J	`jnl`	Value-Directed Belief State Approximation for POMDPs CoRR Pascal Poupart, Craig Boutilier
2013	J	`jnl`	Value-Directed Sampling Methods for POMDPs CoRR Pascal Poupart, Luis E. Ortiz, Craig Boutilier
2013	J	`jnl`	Vector-space Analysis of Belief-state Approximation for POMDPs CoRR Pascal Poupart, Craig Boutilier
2012	—	`ch.`	Bayesian Reinforcement Learning. Reinforcement Learning Nikos Vlassis, Mohammad Ghavamzadeh, Shie Mannor, Pascal Poupart
2012	J	`jnl`	Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker CoRR Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine
2012	—	`conf`	Cost-Sensitive Exploration in Bayesian Reinforcement Learning. NIPS Dongho Kim, Kee-Eung Kim, Pascal Poupart
2012	A*	`conf`	Hierarchical Double Dirichlet Process Mixture of Gaussian Processes. AAAI Aditya Tayal, Pascal Poupart, Yuying Li
2012	J	`jnl`	Hierarchical POMDP Controller Optimization by Likelihood Maximization CoRR Marc Toussaint, Laurent Charlin, Pascal Poupart
2012	J	`jnl`	Introduction to the Issue on Advances in Spoken Dialogue Systems and Mobile Interface. IEEE J. Sel. Top. Signal Process. Jason D. Williams, Kai Yu, Brahim Chaib-draa, Oliver Lemon, Roberto Pieraccini, Olivier Pietquin, Pascal Poupart, Steve J. Young
2012	—	`conf`	Muscle Categorization Using Quantitative Needle Electromyography: A 2-Stage Gaussian Mixture Model Based Approach. ICMLA (1) Meena Abdelmaseeh, Pascal Poupart, Benn Smith, Daniel W. Stashuk
2012	J	`jnl`	People, sensors, decisions: Customizable and adaptive technologies for assistance in healthcare. ACM Trans. Interact. Intell. Syst. Jesse Hoey, Craig Boutilier, Pascal Poupart, Patrick Olivier, Andrew Monk, Alex Mihailidis
2012	—	`conf`	Symbolic Dynamic Programming for Continuous State and Observation POMDPs. NIPS Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting
2011	—	`conf`	3D Pose tracking of walker users' lower limb with a structured-light camera on a moving platform. CVPR Workshops Richard Zhi-Ling Hu, Adam Hartfiel, James Yungjen Tung, Adel H. Fakih, Jesse Hoey, Pascal Poupart
2011	—	`conf`	A bayesian approach to online performance modeling for database appliances using gaussian models. ICAC Muhammad Bilal Sheikh, Umar Farooq Minhas, Omar Zia Khan, Ashraf Aboulnaga, Pascal Poupart, David J. Taylor
2011	—	`conf`	Ambulatory Assessment of Lifestyle Factors for Alzheimer's Disease and Related Dementias. AAAI Spring Symposium: Computational Physiology James Yungjen Tung, Jonathan F. L. Semple, Wei X. Woo, Wei-Shou Hsu, Mathieu Sinn, Eric A. Roy, Pascal Poupart
2011	—	`conf`	Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains. ECML/PKDD (2) Pascal Poupart, Tobias Lang, Marc Toussaint
2011	A	`conf`	Asymptotic Theory for Linear-Chain Conditional Random Fields. AISTATS Mathieu Sinn, Pascal Poupart
2011	—	`conf`	Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints. NIPS Omar Zia Khan, Pascal Poupart, John Mark Agosta
2011	A*	`conf`	Closing the Gap: Improved Bounds on Optimal POMDP Solutions. ICAPS Pascal Poupart, Kee-Eung Kim, Dongho Kim
2011	A*	`conf`	Continuous Correlated Beta Processes. IJCAI Robby Goetschalckx, Pascal Poupart, Jesse Hoey
2011	—	`conf`	Error Bounds for Online Predictions of Linear-Chain Conditional Random Fields: Application to Activity Recognition for Users of Rolling Walkers. ICMLA (2) Mathieu Sinn, Pascal Poupart
2011	A	`conf`	Escaping local optima in POMDP planning as inference. AAMAS Pascal Poupart, Tobias Lang, Marc Toussaint
2011	J	`jnl`	Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference. J. Artif. Intell. Res. Wei Li, Pascal Poupart, Peter van Beek
2011	A*	`conf`	Point-Based Value Iteration for Constrained POMDPs. IJCAI Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart
2011	A	`conf`	Smart walkers!: enhancing the mobility of the elderly. AAMAS Mathieu Sinn, Pascal Poupart
2010	J	`jnl`	Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process. Comput. Vis. Image Underst. Jesse Hoey, Pascal Poupart, Axel von Bertoldi, Tammy Craig, Craig Boutilier, Alex Mihailidis
2010	—	`ch.`	Bayesian Reinforcement Learning. Encyclopedia of Machine Learning Pascal Poupart
2010	A	`conf`	Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker. UAI Farheen Omar, Mathieu Sinn, Jakub Truszkowski, Pascal Poupart, James Yungjen Tung, Allen Caine
2010	—	`ch.`	Partially Observable Markov Decision Processes. Encyclopedia of Machine Learning Pascal Poupart
2009	J	`jnl`	AAAI 2008 Workshop Reports. AI Mag. 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, Rong Zhou
2009	A*	`conf`	Minimal Sufficient Explanations for Factored Markov Decision Processes. ICAPS Omar Zia Khan, Pascal Poupart, James P. Black
2009	—	`conf`	Minimal Sufficient Explanations for MDPs. ExaCt Omar Zia Khan, Pascal Poupart, James P. Black
2009	—	`conf`	Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images. CRV Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal Poupart, John S. Zelek
2008	A*	`conf`	Efficient ADD Operations for Point-Based Algorithms. ICAPS Guy Shani, Pascal Poupart, Ronen I. Brafman, Solomon Eyal Shimony
2008	—	`conf`	Explaining recommendations generated by MDPs. ExaCt Omar Zia Khan, Pascal Poupart, James P. Black
2008	A*	`conf`	Exploiting Causal Independence Using Weighted Model Counting. AAAI Wei Li, Pascal Poupart, Peter van Beek
2008	A	`conf`	Hierarchical POMDP Controller Optimization by Likelihood Maximization. UAI Marc Toussaint, Laurent Charlin, Pascal Poupart
2008	A*	`conf`	Is the sky pure today? AwkChecker: an assistive tool for detecting and correcting collocation errors. UIST Taehyun Park, Edward Lank, Pascal Poupart, Michael A. Terry
2008	Misc	`conf`	Model-based Bayesian Reinforcement Learning in Partially Observable Domains. ISAIM Pascal Poupart, Nikos Vlassis
2007	—	`conf`	Generating Lexical Analogies Using Dependency Relations. EMNLP-CoNLL Andy Chiu, Pascal Poupart, Chrysanne DiMarco
2006	J	`jnl`	A Planning System Based on Markov Decision Processes to Guide People With Dementia Through Activities of Daily Living. IEEE Trans. Inf. Technol. Biomed. Jennifer Boger, Jesse Hoey, Pascal Poupart, Craig Boutilier, Geoff R. Fernie, Alex Mihailidis
2006	A*	`conf`	An analytic solution to discrete Bayesian reinforcement learning. ICML Pascal Poupart, Nikos Vlassis, Jesse Hoey, Kevin Regan
2006	—	`conf`	Automated Hierarchy Discovery for Planning in Partially Observable Environments. NIPS Laurent Charlin, Pascal Poupart, Romy Shioda
2006	A*	`conf`	Bayesian Reputation Modeling in E-Marketplaces Sensitive to Subjectivity, Deception and Change. AAAI Kevin Regan, Pascal Poupart, Robin Cohen
2006	A*	`conf`	Compact, Convex Upper Bound Iteration for Approximate POMDP Planning. AAAI Tao Wang, Pascal Poupart, Michael H. Bowling, Dale Schuurmans
2006	J	`jnl`	Constraint-based optimization and utility elicitation using the minimax decision criterion. Artif. Intell. Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans
2006	A*	`conf`	Performing Incremental Bayesian Inference by Dynamic Model Counting. AAAI Wei Li, Peter van Beek, Pascal Poupart
2006	J	`jnl`	Point-Based Value Iteration for Continuous POMDPs. J. Mach. Learn. Res. Josep M. Porta, Nikos Vlassis, Matthijs T. J. Spaan, Pascal Poupart
2006	J	`jnl`	Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program. AI Mag. Wolfgang Achtner, Esma Aïmeur, Sarabjot Singh Anand, Douglas E. 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 J. Young, Dmitry Zelenko
2005	A*	`conf`	A Decision-Theoretic Approach to Task Assistance for Persons with Dementia. IJCAI Jennifer Boger, Pascal Poupart, Jesse Hoey, Craig Boutilier, Geoff R. Fernie, Alex Mihailidis
2005	—	`—`	Exploiting structure to efficiently solve large scale partially observable Markov decision processes. Pascal Poupart
2005	—	`conf`	POMDP Models for Assistive Technology. AAAI Fall Symposium: Caring Machines Jesse Hoey, Pascal Poupart, Craig Boutilier, Alex Mihailidis
2005	—	`conf`	Partially Observable Markov Decision Processes with Continuous Observations for Dialogue Management. SIGDIAL Workshop Jason D. Williams, Pascal Poupart, Steve J. Young
2005	A*	`conf`	Regret-based Utility Elicitation in Constraint-based Decision Problems. IJCAI Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans
2005	A*	`conf`	Solving POMDPs with Continuous or Large Discrete Observation Spaces. IJCAI Jesse Hoey, Pascal Poupart
2005	C	`conf`	The Advisor-POMDP: A Principled Approach to Trust through Reputation in Electronic Markets. PST Kevin Regan, Robin Cohen, Pascal Poupart
2004	—	`conf`	VDCBPI: an Approximate Scalable Algorithm for Large POMDPs. NIPS Pascal Poupart, Craig Boutilier
2003	—	`conf`	Bounded Finite State Controllers. NIPS Pascal Poupart, Craig Boutilier
2003	A	`conf`	Constraint-Based Optimization with the Minimax Decision Criterion. CP Craig Boutilier, Relu Patrascu, Pascal Poupart, Dale Schuurmans
2002	—	`conf`	Greedy Linear Value-Approximation for Factored Markov Decision Processes. AAAI/IAAI Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier, Carlos Guestrin
2002	—	`conf`	Piecewise Linear Value Function Approximation for Factored MDPs. AAAI/IAAI Pascal Poupart, Craig Boutilier, Relu Patrascu, Dale Schuurmans
2002	—	`conf`	Value-Directed Compression of POMDPs. NIPS Pascal Poupart, Craig Boutilier
2001	A	`conf`	Value-Directed Sampling Methods for POMDPs. UAI Pascal Poupart, Luis E. Ortiz, Craig Boutilier
2001	A	`conf`	Vector-space Analysis of Belief-state Approximation for POMDPs. UAI Pascal Poupart, Craig Boutilier
2000	A	`conf`	Value-Directed Belief State Approximation for POMDPs. UAI Pascal Poupart, Craig Boutilier