papers

Publications (91)

cs.LG2026

Counterfactual Residual Data Augmentation for Regression

Hossein Mohebbi, Oliver Schulte, Ke Li +1

cs.LG2023

NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge

Xiangyu Sun, Oliver Schulte, Guiliang Liu +1

cs.LG2024

Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space

Mohsin Hasan, Guojun Zhang, Kaiyang Guo +2

cs.CL2015

Self-Adaptive Hierarchical Sentence Model

Han Zhao, Zhengdong Lu, Pascal Poupart

cs.AI2013

Value-Directed Belief State Approximation for POMDPs

Pascal Poupart, Craig Boutilier

cs.LG2016

Dynamic Sum Product Networks for Tractable Inference on Sequence Data (Extended Version)

Mazen Melibari, Pascal Poupart, Prashant Doshi +1

cs.LG2022

Learning Functions on Multiple Sets using Multi-Set Transformers

Kira Selby, Ahmad Rashid, Ivan Kobyzev +2

cs.CV2018

Unsupervised Video Object Segmentation for Deep Reinforcement Learning

Vik Goel, Jameson Weng, Pascal Poupart

cs.CV2024

Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning

Yanting Miao, William Loh, Suraj Kothawade +3

cs.AI2015

On the Relationship between Sum-Product Networks and Bayesian Networks

Han Zhao, Mazen Melibari, Pascal Poupart

cs.CV2026

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models

Yanting Miao, Yutao Sun, Dexin Wang +8

cs.LG2024

Label Alignment Regularization for Distribution Shift

Ehsan Imani, Guojun Zhang, Runjia Li +4

cs.GT2025

Policy-Conditioned Policies for Multi-Agent Task Solving

Yue Lin, Shuhui Zhu, Wenhao Li +5

cs.CV2019

Matrix Nets: A New Deep Architecture for Object Detection

Abdullah Rashwan, Agastya Kalra, Pascal Poupart

cs.MA2021

Partially Observable Mean Field Reinforcement Learning

Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley +1

cs.LG2016

A Unified Approach for Learning the Parameters of Sum-Product Networks

Han Zhao, Pascal Poupart, Geoff Gordon

cs.AI2026

ACPO: Agent-Chained Policy Optimization for Multi-Agent Reinforcement Learning

Daiki E. Matsunaga, Junho Na, Tri Wahyu Guntara +4

cs.LG2023

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient

Yudong Luo, Guiliang Liu, Pascal Poupart +1

cs.GT2025

Information Bargaining: Bilateral Commitment in Bayesian Persuasion

Yue Lin, Shuhui Zhu, William A Cunningham +4

cs.CL2020

Progressive Memory Banks for Incremental Domain Adaptation

Nabiha Asghar, Lili Mou, Kira A. Selby +3

cs.CL2023

Attribute Controlled Dialogue Prompting

Runcheng Liu, Ahmad Rashid, Ivan Kobyzev +2

cs.AI2016

Online and Distributed learning of Gaussian mixture models by Bayesian Moment Matching

Priyank Jaini, Pascal Poupart

cs.LG2026

The Reciprocity Gradient

Yue Lin, Pascal Poupart, Shuhui Zhu +5

cs.CL2017

Order-Planning Neural Text Generation From Structured Data

Lei Sha, Lili Mou, Tianyu Liu +4

stat.ML2017

Online Structure Learning for Sum-Product Networks with Gaussian Leaves

Wilson Hsu, Agastya Kalra, Pascal Poupart

cs.LG2018

On Improving Deep Reinforcement Learning for POMDPs

Pengfei Zhu, Xin Li, Pascal Poupart +1

cs.LG2019

Comparing EM with GD in Mixture Models of Two Components

Guojun Zhang, Pascal Poupart, George Trimponias

cs.LG2025

Towards Cost-Effective Reward Guided Text Generation

Ahmad Rashid, Ruotian Wu, Rongqi Fan +3

cs.MA2022

Decentralized Mean Field Games

Sriram Ganapathi Subramanian, Matthew E. Taylor, Mark Crowley +1

cs.LG2023

Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks

Xiangle Cheng, James He, Shihan Xiao +4

cs.AI2013

Value-Directed Sampling Methods for POMDPs

Pascal Poupart, Luis E. Ortiz, Craig Boutilier

cs.LG2024

Why Online Reinforcement Learning is Causal

Oliver Schulte, Pascal Poupart

cs.LG2023

Do we need Label Regularization to Fine-tune Pre-trained Language Models?

Ivan Kobyzev, Aref Jafari, Mehdi Rezagholizadeh +5

cs.LG2024

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?

Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta +3

cs.LG2023

Benchmarking Constraint Inference in Inverse Reinforcement Learning

Guiliang Liu, Yudong Luo, Ashish Gaurav +2

cs.CL2020

Unsupervised Multilingual Alignment using Wasserstein Barycenter

Xin Lian, Kshitij Jain, Jakub Truszkowski +2

cs.CV2025

Image-POSER: Reflective RL for Multi-Expert Image Generation and Editing

Hossein Mohebbi, Mohammed Abdulrahman, Yanting Miao +2

cs.CL2016

Discovering Conversational Dependencies between Messages in Dialogs

Wenchao Du, Pascal Poupart, Wei Xu

cs.AI2013

Vector-space Analysis of Belief-state Approximation for POMDPs

Pascal Poupart, Craig Boutilier

cs.LG2019

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

Alejandro Molina, Antonio Vergari, Karl Stelzner +5

cs.LG2022

Federated Bayesian Neural Regression: A Scalable Global Federated Gaussian Process

Haolin Yu, Kaiyang Guo, Mahdi Karami +3

cs.CL2021

Learning Dynamic Belief Graphs to Generalize on Text-Based Games

Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté +7

cs.MA2026

Talk, Judge, Cooperate: Gossip-Driven Indirect Reciprocity in Self-Interested LLM Agents

Shuhui Zhu, Yue Lin, Shriya Kaistha +5

cs.CL2025

Time Is Effort: Estimating Human Post-Editing Time for Grammar Error Correction Tool Evaluation

Ankit Vadehra, Bill Johnson, Gene Saunders +1

cs.MA2022

Multi Type Mean Field Reinforcement Learning

Sriram Ganapathi Subramanian, Pascal Poupart, Matthew E. Taylor +1

cs.CL2022

CILDA: Contrastive Data Augmentation using Intermediate Layer Knowledge Distillation

Md Akmal Haidar, Mehdi Rezagholizadeh, Abbas Ghaddar +3

cs.AI2014

Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference

Wei Li, Pascal Poupart, Peter van Beek

cs.CL2017

Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation

Bolin Wei, Shuai Lu, Lili Mou +4

cs.LG2026

A Practical Algorithm for Feature-Rich, Non-Stationary Bandit Problems

Wei Min Loh, Sajib Kumer Sinha, Ankur Agarwal +1

cs.LG2024

Confidence Aware Inverse Constrained Reinforcement Learning

Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi +2

cs.CL2017

Deep Active Learning for Dialogue Generation

Nabiha Asghar, Pascal Poupart, Xin Jiang +1

cs.HC2025

Chrysalis: A Unified System for Comparing Active Teaching and Passive Learning with AI Agents in Education

Prashanth Arun, Vinita Vader, Erya Xu +6

cs.LG2022

Robust One Round Federated Learning with Predictive Space Bayesian Inference

Mohsin Hasan, Zehao Zhang, Kaiyang Guo +4

math.OC2020

A Positivstellensatz for Conditional SAGE Signomials

Allen Houze Wang, Priyank Jaini, Yaoliang Yu +1

cs.AI2012

Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker

Farheen Omar, Mathieu Sinn, Jakub Truszkowski +3

cs.LG2024

FedLog: Personalized Federated Classification with Less Communication and More Flexibility

Haolin Yu, Guojun Zhang, Pascal Poupart

cs.CL2021

Robust Embeddings Via Distributions

Kira A. Selby, Yinong Wang, Ruizhe Wang +4

cs.LG2023

Learning Soft Constraints From Constrained Expert Demonstrations

Ashish Gaurav, Kasra Rezaee, Guiliang Liu +1

cs.CL2020

Generating Emotionally Aligned Responses in Dialogues using Affect Control Theory

Nabiha Asghar, Ivan Kobyzev, Jesse Hoey +2

cs.CL2018

Variational Attention for Sequence-to-Sequence Models

Hareesh Bahuleyan, Lili Mou, Olga Vechtomova +1

cs.LG2025

Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling

Gustavo Sutter Pessurno de Carvalho, Mohammed Abdulrahman, Hao Wang +7

cs.AI2025

Learning to Negotiate via Voluntary Commitment

Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian +1

cs.CV2021

Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map

Elmira Amirloo, Mohsen Rohani, Ershad Banijamali +2

cs.LG2019

Time2Vec: Learning a Vector Representation of Time

Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali +7

cs.AI2025

Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens

Jihwan Jeong, Xiaoyu Wang, Jingmin Wang +2

cs.LG2023

Newton-type Methods for Minimax Optimization

Guojun Zhang, Kaiwen Wu, Pascal Poupart +1

cs.CL2017

Affective Neural Response Generation

Nabiha Asghar, Pascal Poupart, Jesse Hoey +2

cs.LG2024

A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization

Yudong Luo, Yangchen Pan, Han Wang +2

cs.LG2025

Uncertainty-Guided Likelihood Tree Search

Julia Grosse, Ruotian Wu, Ahmad Rashid +4

cs.CV2020

MatrixNets: A New Scale and Aspect Ratio Aware Architecture for Object Detection

Abdullah Rashwan, Rishav Agarwal, Agastya Kalra +1

cs.LG2022

Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization

Aref Jafari, Ivan Kobyzev, Mehdi Rezagholizadeh +2

cs.LG2021

Batch norm with entropic regularization turns deterministic autoencoders into generative models

Amur Ghose, Abdullah Rashwan, Pascal Poupart

cs.LG2017

Generative Mixture of Networks

Ershad Banijamali, Ali Ghodsi, Pascal Poupart

cs.LG2023

FedFormer: Contextual Federation with Attention in Reinforcement Learning

Liam Hebert, Lukasz Golab, Pascal Poupart +1

cs.LG2021

Quantifying and Improving Transferability in Domain Generalization

Guojun Zhang, Han Zhao, Yaoliang Yu +1

cs.CL2021

RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation

Md Akmal Haidar, Nithin Anchuri, Mehdi Rezagholizadeh +3

cs.AI2012

Hierarchical POMDP Controller Optimization by Likelihood Maximization

Marc Toussaint, Laurent Charlin, Pascal Poupart

cs.LG2026

Out-Of-The-Loop Multi-Fidelity Bayesian Optimization

Gustavo Sutter, Hao Wang, Luis Ricardez-Sandoval +2

cs.LG2025

Measures of Variability for Risk-averse Policy Gradient

Yudong Luo, Yangchen Pan, Jiaqi Tan +1

cs.LG2014

A Sober Look at Spectral Learning

Han Zhao, Pascal Poupart

cs.LG2020

Representation Learning for Dynamic Graphs: A Survey

Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain +4

cs.LG2024

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

Agustinus Kristiadi, Felix Strieth-Kalthoff, Sriram Ganapathi Subramanian +3

cs.LG2025

Basis Transformers for Multi-Task Tabular Regression

Wei Min Loh, Jiaqi Shang, Pascal Poupart

cs.LG2018

On Improving Deep Reinforcement Learning for POMDPs

Pengfei Zhu, Xin Li, Pascal Poupart +1

cs.LG2019

Diachronic Embedding for Temporal Knowledge Graph Completion

Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker +1

cs.LG2025

A Critical Look At Tokenwise Reward-Guided Text Generation

Ahmad Rashid, Ruotian Wu, Julia Grosse +2

cs.LG2025

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

Guiliang Liu, Sheng Xu, Shicheng Liu +3

cs.RO2024

Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories

Niloufar Saeidi Mobarakeh, Behzad Khamidehi, Chunlin Li +6

cs.LG2024

Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks

Ahmad Rashid, Serena Hacker, Guojun Zhang +2

cs.LG2022

Optimality and Stability in Non-Convex Smooth Games

Guojun Zhang, Pascal Poupart, Yaoliang Yu

cs.LG2020

Prediction by Anticipation: An Action-Conditional Prediction Method based on Interaction Learning

Ershad Banijamali, Mohsen Rohani, Elmira Amirloo +2