Pascal Poupart

Affiliations:
  • University of Waterloo, ON, Canada


According to our database1, Pascal Poupart authored at least 186 papers between 2000 and 2024.

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Bibliography

2024
Label Alignment Regularization for Distribution Shift.
J. Mach. Learn. Res., 2024

A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges.
CoRR, 2024

Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning.
CoRR, 2024

FedLog: Personalized Federated Classification with Less Communication and More Flexibility.
CoRR, 2024

Uncertainty-Guided Optimization on Large Language Model Search Trees.
CoRR, 2024

A Critical Look At Tokenwise Reward-Guided Text Generation.
CoRR, 2024

How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?
CoRR, 2024

Why Online Reinforcement Learning is Causal.
CoRR, 2024

A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization.
RLJ, 2024

Confidence Aware Inverse Constrained Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Batchnorm Allows Unsupervised Radial Attacks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Benchmarking Constraint Inference in Inverse Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Soft Constraints From Constrained Expert Demonstrations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Contrastive Deterministic Autoencoders For Language Modeling.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Do we need Label Regularization to Fine-tune Pre-trained Language Models?
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Defensive Collaborative Learning: Protecting Objective Privacy in Data Sharing.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

FedFormer: Contextual Federation with Attention in Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Attribute Controlled Dialogue Prompting.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Optimality and Stability in Non-Convex Smooth Games.
J. Mach. Learn. Res., 2022

Label Alignment Regularization for Distribution Shift.
CoRR, 2022

Robust One Round Federated Learning with Predictive Space Bayesian Inference.
CoRR, 2022

Federated Bayesian Neural Regression: A Scalable Global Federated Gaussian Process.
CoRR, 2022

Towards Understanding Label Regularization for Fine-tuning Pre-trained Language Models.
CoRR, 2022

Learning functions on multiple sets using multi-set transformers.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Linearizing contextual bandits with latent state dynamics.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Distributional Reinforcement Learning with Monotonic Splines.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Object-Oriented Dynamics for Planning from Text.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

CILDA: Contrastive Data Augmentation Using Intermediate Layer Knowledge Distillation.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

WatClaimCheck: A new Dataset for Claim Entailment and Inference.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Decentralized Mean Field Games.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks.
CoRR, 2021

NTS-NOTEARS: Learning Nonparametric Temporal DAGs With Time-Series Data and Prior Knowledge.
CoRR, 2021

Robust Embeddings Via Distributions.
CoRR, 2021

Quantifying and Improving Transferability in Domain Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Tree Interpretation from Object Representation for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Partially Observable Mean Field Reinforcement Learning.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
Representation Learning for Dynamic Graphs: A Survey.
J. Mach. Learn. Res., 2020

Learning directed acyclic graph SPNs in sub-quadratic time.
Int. J. Approx. Reason., 2020

Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch.
Int. J. Approx. Reason., 2020

Newton-type Methods for Minimax Optimization.
CoRR, 2020

Complete Hierarchy of Relaxation for Constrained Signomial Positivity.
CoRR, 2020

Generating Emotionally Aligned Responses in Dialogues using Affect Control Theory.
CoRR, 2020

Optimality and Stability in Non-Convex-Non-Concave Min-Max Optimization.
CoRR, 2020

Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games.
CoRR, 2020

MatrixNets: A New Scale and Aspect Ratio Aware Architecture for Object Detection.
CoRR, 2020

Batch norm with entropic regularization turns deterministic autoencoders into generative models.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Learning Agent Representations for Ice Hockey.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Dynamic Belief Graphs to Generalize on Text-Based Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Unsupervised Multilingual Alignment using Wasserstein Barycenter.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Online Bayesian Moment Matching based SAT Solver Heuristics.
Proceedings of the 37th International Conference on Machine Learning, 2020

Progressive Memory Banks for Incremental Domain Adaptation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Multi Type Mean Field Reinforcement Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Diachronic Embedding for Temporal Knowledge Graph Completion.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Time2Vec: Learning a Vector Representation of Time.
CoRR, 2019

Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey.
CoRR, 2019

SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks.
CoRR, 2019

Comparing EM with GD in Mixture Models of Two Components.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

On the Relationship Between Satisfiability and Markov Decision Processes.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Matrix Nets: A New Deep Architecture for Object Detection.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Why Do Neural Dialog Systems Generate Short and Meaningless Replies? a Comparison between Dialog and Translation.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Discriminative Training of Sum-Product Networks by Extended Baum-Welch.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

An Empirical Study of Methods for SPN Learning and Inference.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Monte-Carlo Tree Search for Constrained POMDPs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Homogeneous Mixture Models: Representation, Separation, and Approximation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Unsupervised Video Object Segmentation for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An Empirical Study of Branching Heuristics through the Lens of Global Learning Rate.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Affective Neural Response Generation.
Proceedings of the Advances in Information Retrieval, 2018

Variational Attention for Sequence-to-Sequence Models.
Proceedings of the 27th International Conference on Computational Linguistics, 2018

Faster Policy Adaptation in Environments with Exogeneity: A State Augmentation Approach.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Order-Planning Neural Text Generation From Structured Data.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Partially Observable Markov Decision Processes.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Bayesian Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

On Improving Deep Reinforcement Learning for POMDPs.
CoRR, 2017

Deep Active Learning for Dialogue Generation.
Proceedings of the 6th Joint Conference on Lexical and Computational Semantics, 2017

A Propagation Rate Based Splitting Heuristic for Divide-and-Conquer Solvers.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2017 - 20th International Conference, Melbourne, VIC, Australia, August 28, 2017

An Empirical Study of Branching Heuristics Through the Lens of Global Learning Rate.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2017 - 20th International Conference, Melbourne, VIC, Australia, August 28, 2017

Generative mixture of networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Constrained Bayesian Reinforcement Learning via Approximate Linear Programming.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Online Bayesian Transfer Learning for Sequential Data Modeling.
Proceedings of the 5th International Conference on Learning Representations, 2017

Online Structure Learning for Sum-Product Networks with Gaussian Leaves.
Proceedings of the 5th International Conference on Learning Representations, 2017

Discovering Conversational Dependencies between Messages in Dialogs.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Online and Distributed learning of Gaussian mixture models by Bayesian Moment Matching.
CoRR, 2016

Online Sequence-to-Sequence Active Learning for Open-Domain Dialogue Generation.
CoRR, 2016

Overfitting at SemEval-2016 Task 3: Detecting Semantically Similar Questions in Community Question Answering Forums with Word Embeddings.
Proceedings of the 10th International Workshop on Semantic Evaluation, 2016

Learning Rate Based Branching Heuristic for SAT Solvers.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2016, 2016

Dynamic Sum Product Networks for Tractable Inference on Sequence Data.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Online Algorithms for Sum-Product Networks with Continuous Variables.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

A Unified Approach for Learning the Parameters of Sum-Product Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sum-Product-Max Networks for Tractable Decision Making.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Online flow size prediction for improved network routing.
Proceedings of the 24th IEEE International Conference on Network Protocols, 2016

Sum-Product-Max Networks for Tractable Decision Making: (Extended Abstract).
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Decision Sum-Product-Max Networks.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Exponential Recency Weighted Average Branching Heuristic for SAT Solvers.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Energy Efficient Execution of POMDP Policies.
IEEE Trans. Cybern., 2015

Dynamic Sum Product Networks for Tractable Inference on Sequence Data.
CoRR, 2015

Think fast - resource constrained reasoning and planning under uncertainty.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2015

Self-Adaptive Hierarchical Sentence Model.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

On the Relationship between Sum-Product Networks and Bayesian Networks.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Incremental Policy Iteration with Guaranteed Escape from Local Optima in POMDP Planning.
Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
A Sober Look at Spectral Learning.
CoRR, 2014

Policy optimization by marginal-map probabilistic inference in generative models.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

POMDP planning and execution in an augmented space.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

A Novel Single-DBN Generative Model for Optimizing POMDP Controllers by Probabilistic Inference.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Iterative Model Refinement of Recommender MDPs Based on Expert Feedback.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Isomorph-Free Branch and Bound Search for Finite State Controllers.
Proceedings of the IJCAI 2013, 2013

Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes.
Proceedings of the IJCAI 2013, 2013

Controller Compilation and Compression for Resource Constrained Applications.
Proceedings of the Algorithmic Decision Theory - Third International Conference, 2013

2012
People, sensors, decisions: Customizable and adaptive technologies for assistance in healthcare.
ACM Trans. Interact. Intell. Syst., 2012

Introduction to the Issue on Advances in Spoken Dialogue Systems and Mobile Interface.
IEEE J. Sel. Top. Signal Process., 2012

Symbolic Dynamic Programming for Continuous State and Observation POMDPs.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Cost-Sensitive Exploration in Bayesian Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Muscle Categorization Using Quantitative Needle Electromyography: A 2-Stage Gaussian Mixture Model Based Approach.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Hierarchical Double Dirichlet Process Mixture of Gaussian Processes.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

Bayesian Reinforcement Learning.
Proceedings of the Reinforcement Learning, 2012

2011
Asymptotic Theory for Linear-Chain Conditional Random Fields.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference.
J. Artif. Intell. Res., 2011

Analyzing and Escaping Local Optima in Planning as Inference for Partially Observable Domains.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Point-Based Value Iteration for Constrained POMDPs.
Proceedings of the IJCAI 2011, 2011

Continuous Correlated Beta Processes.
Proceedings of the IJCAI 2011, 2011

Error Bounds for Online Predictions of Linear-Chain Conditional Random Fields: Application to Activity Recognition for Users of Rolling Walkers.
Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

A bayesian approach to online performance modeling for database appliances using gaussian models.
Proceedings of the 8th International Conference on Autonomic Computing, 2011

3D Pose tracking of walker users' lower limb with a structured-light camera on a moving platform.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011

Smart walkers!: enhancing the mobility of the elderly.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

Escaping local optima in POMDP planning as inference.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

Closing the Gap: Improved Bounds on Optimal POMDP Solutions.
Proceedings of the 21st International Conference on Automated Planning and Scheduling, 2011

Ambulatory Assessment of Lifestyle Factors for Alzheimer's Disease and Related Dementias.
Proceedings of the Computational Physiology, 2011

2010
Partially Observable Markov Decision Processes.
Proceedings of the Encyclopedia of Machine Learning, 2010

Bayesian Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process.
Comput. Vis. Image Underst., 2010

Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker.
Proceedings of the UAI 2010, 2010

2009
AAAI 2008 Workshop Reports.
AI Mag., 2009

Minimal Sufficient Explanations for MDPs.
Proceedings of the Explanation-aware Computing, 2009

Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images.
Proceedings of the Sixth Canadian Conference on Computer and Robot Vision, 2009

Minimal Sufficient Explanations for Factored Markov Decision Processes.
Proceedings of the 19th International Conference on Automated Planning and Scheduling, 2009

2008
Is the sky pure today? AwkChecker: an assistive tool for detecting and correcting collocation errors.
Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology, 2008

Hierarchical POMDP Controller Optimization by Likelihood Maximization.
Proceedings of the UAI 2008, 2008

Model-based Bayesian Reinforcement Learning in Partially Observable Domains.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Explaining recommendations generated by MDPs.
Proceedings of the Explanation-aware Computing, 2008

Efficient ADD Operations for Point-Based Algorithms.
Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, 2008

Exploiting Causal Independence Using Weighted Model Counting.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Generating Lexical Analogies Using Dependency Relations.
Proceedings of the EMNLP-CoNLL 2007, 2007

2006
A Planning System Based on Markov Decision Processes to Guide People With Dementia Through Activities of Daily Living.
IEEE Trans. Inf. Technol. Biomed., 2006

Point-Based Value Iteration for Continuous POMDPs.
J. Mach. Learn. Res., 2006

Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program.
AI Mag., 2006

Constraint-based optimization and utility elicitation using the minimax decision criterion.
Artif. Intell., 2006

Automated Hierarchy Discovery for Planning in Partially Observable Environments.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

An analytic solution to discrete Bayesian reinforcement learning.
Proceedings of the Machine Learning, 2006

Compact, Convex Upper Bound Iteration for Approximate POMDP Planning.
Proceedings of the Proceedings, 2006

Bayesian Reputation Modeling in E-Marketplaces Sensitive to Subjectivity, Deception and Change.
Proceedings of the Proceedings, 2006

Performing Incremental Bayesian Inference by Dynamic Model Counting.
Proceedings of the Proceedings, 2006

2005
Exploiting structure to efficiently solve large scale partially observable Markov decision processes.
PhD thesis, 2005

Partially Observable Markov Decision Processes with Continuous Observations for Dialogue Management.
Proceedings of the 6th SIGdial Workshop on Discourse and Dialogue, 2005

The Advisor-POMDP: A Principled Approach to Trust through Reputation in Electronic Markets.
Proceedings of the Third Annual Conference on Privacy, 2005

Solving POMDPs with Continuous or Large Discrete Observation Spaces.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Regret-based Utility Elicitation in Constraint-based Decision Problems.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

A Decision-Theoretic Approach to Task Assistance for Persons with Dementia.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

POMDP Models for Assistive Technology.
Proceedings of the Caring Machines: AI in Eldercare, 2005

2004
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Bounded Finite State Controllers.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Constraint-Based Optimization with the Minimax Decision Criterion.
Proceedings of the Principles and Practice of Constraint Programming, 2003

2002
Value-Directed Compression of POMDPs.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Piecewise Linear Value Function Approximation for Factored MDPs.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

Greedy Linear Value-Approximation for Factored Markov Decision Processes.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
Value-Directed Sampling Methods for POMDPs.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Vector-space Analysis of Belief-state Approximation for POMDPs.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

2000
Value-Directed Belief State Approximation for POMDPs.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000


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