Paul Weng

Orcid: 0000-0002-2008-4569

According to our database1, Paul Weng authored at least 74 papers between 2005 and 2024.

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Bibliography

2024
Revisiting Data Augmentation in Deep Reinforcement Learning.
CoRR, 2024

INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer.
CoRR, 2024

2023
Analytics and machine learning in vehicle routing research.
Int. J. Prod. Res., 2023

A Survey of Reinforcement Learning from Human Feedback.
CoRR, 2023

Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Improving Subtour Elimination Constraint Generation in Branch-and-Cut Algorithms for the TSP with Machine Learning.
Proceedings of the Learning and Intelligent Optimization - 17th International Conference, 2023

Fair Deep Reinforcement Learning with Preferential Treatment.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
A comparative study of linearization methods for Ordered Weighted Average.
Proceedings of the 12th International Workshop on Resilient Networks Design and Modeling, 2022

Neuro-Symbolic Hierarchical Rule Induction.
Proceedings of the International Conference on Machine Learning, 2022

Planning with Q-Values in Sparse Reward Reinforcement Learning.
Proceedings of the Intelligent Robotics and Applications - 15th International Conference, 2022

Solving Complex Manipulation Tasks with Model-Assisted Model-Free Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 2022

CVaR-Regret Bounds for Multi-armed Bandits.
Proceedings of the Asian Conference on Machine Learning, 2022

2021
Hyperparameter Auto-Tuning in Self-Supervised Robotic Learning.
IEEE Robotics Autom. Lett., 2021

Neuro-Symbolic Hierarchical Rule Induction.
CoRR, 2021

A Survey on Interpretable Reinforcement Learning.
CoRR, 2021

Generalization in Deep RL for TSP Problems via Equivariance and Local Search.
CoRR, 2021

Learning Symbolic Rules for Interpretable Deep Reinforcement Learning.
CoRR, 2021

Differentiable Logic Machines.
CoRR, 2021

Improving Generalization of Deep Reinforcement Learning-based TSP Solvers.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Safe Distributional Reinforcement Learning.
Proceedings of the Distributed Artificial Intelligence - Third International Conference, 2021

2020
Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning.
IEEE Robotics Autom. Lett., 2020

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2020

Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewards.
CoRR, 2020

Reinforcement Learning.
CoRR, 2020

Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards.
Proceedings of the 37th International Conference on Machine Learning, 2020

Decomposed Deep Reinforcement Learning for Robotic Control.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation.
CoRR, 2019

Invariant Transform Experience Replay.
CoRR, 2019

Fairness in Reinforcement Learning.
CoRR, 2019

Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems.
Proceedings of the World Wide Web Conference, 2019

Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

An efficient reinforcement learning algorithm for learning deterministic policies in continuous domains.
Proceedings of the First International Conference on Distributed Artificial Intelligence, 2019

2018
Hierarchical Electric Vehicle Charging Aggregator Strategy Using Dantzig-Wolfe Decomposition.
IEEE Des. Test, 2018

Representing Relative Visual Attributes with a Reference-Point-Based Decision Model.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

Mediation of Debates with Dynamic Argumentative Behaviors.
Proceedings of the Computational Models of Argument, 2018

Adversarial Training Model Unifying Feature Driven and Point Process Perspectives for Event Popularity Prediction.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Functional Reward Markov Decision Processes: Theory and Applications.
Int. J. Artif. Intell. Tools, 2017

Optimal Threshold Policies for Robust Data Center Control.
CoRR, 2017

Multi-objective Bandits: Optimizing the Generalized Gini Index.
Proceedings of the 34th International Conference on Machine Learning, 2017

An Efficient Primal-Dual Algorithm for Fair Combinatorial Optimization Problems.
Proceedings of the Combinatorial Optimization and Applications, 2017

Optimizing Quantiles in Preference-Based Markov Decision Processes.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Quantile Reinforcement Learning.
CoRR, 2016

Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

From Preference-Based to Multiobjective Sequential Decision-Making.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2016

Finding Risk-Averse Shortest Path with Time-Dependent Stochastic Costs.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2016

2015
Reports of the AAAI 2014 Conference Workshops.
AI Mag., 2015

Optimization of Probabilistic Argumentation with Markov Decision Models.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Solving MDPs with Skew Symmetric Bilinear Utility Functions.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Qualitative Multi-Armed Bandits: A Quantile-Based Approach.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Reducing the Number of Queries in Interactive Value Iteration.
Proceedings of the Algorithmic Decision Theory - 4th International Conference, 2015

2014
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm.
Mach. Learn., 2014

Solving Hidden-Semi-Markov-Mode Markov Decision Problems.
Proceedings of the Scalable Uncertainty Management - 8th International Conference, 2014

Preface.
Proceedings of the Multidisciplinary Workshop on Advances in Preference Handling, 2014

2013
A Compromise Programming Approach to multiobjective Markov Decision Processes.
Int. J. Inf. Technol. Decis. Mak., 2013

Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Axiomatic Foundations of Generalized Qualitative Utility.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2013

Markov Decision Processes with Functional Rewards.
Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2013

Interactive Value Iteration for Markov Decision Processes with Unknown Rewards.
Proceedings of the IJCAI 2013, 2013

Top-k Selection based on Adaptive Sampling of Noisy Preferences.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
On WOWA Rank Reversal.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2012

Ordinal Decision Models for Markov Decision Processes.
Proceedings of the ECAI 2012, 2012

2011
On Minimizing Ordered Weighted Regrets in Multiobjective Markov Decision Processes.
Proceedings of the Algorithmic Decision Theory - Second International Conference, 2011

Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation.
Proceedings of the Algorithmic Decision Theory - Second International Conference, 2011

Markov Decision Processes with Ordinal Rewards: Reference Point-Based Preferences.
Proceedings of the 21st International Conference on Automated Planning and Scheduling, 2011

2010
On Finding Compromise Solutions in Multiobjective Markov Decision Processes.
Proceedings of the ECAI 2010, 2010

2007
Conditions générales pour l'admissibilité de la programmation dynamique dans la décision séquentielle possibiliste.
Rev. d'Intelligence Artif., 2007

2006
Processus de décision markoviens et préférences non classiques.
Rev. d'Intelligence Artif., 2006

Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility.
Proceedings of the UAI '06, 2006

An Axiomatic Approach in Qualitative Decision Theory with Binary Possibilistic Utility.
Proceedings of the ECAI 2006, 17th European Conference on Artificial Intelligence, August 29, 2006

2005
Qualitative Decision Making Under Possibilistic Uncertainty: Toward more Discriminating Criteria.
Proceedings of the UAI '05, 2005

Algebraic Markov Decision Processes.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005


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