Paul Weng

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 67

Top Topics

Markov Decision Process

Reinforcement Learning

Top Venues

Publications

Zhaohui Jiang, Paul Weng
Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning. CoRR (2024)
Yunpeng Jiang, Paul Weng, Yutong Ban
Enhancing Class Fairness in Classification with A Two-Player Game Approach. CoRR (2024)
Wenbin Ouyang, Yisen Wang, Paul Weng, Shaochen Han
Generalization in Deep RL for TSP Problems via Equivariance and Local Search. SN Comput. Sci. 5 (4) (2024)
Jianshu Hu, Yunpeng Jiang, Paul Weng
Revisiting Data Augmentation in Deep Reinforcement Learning. CoRR (2024)
Claire Glanois, Paul Weng, Matthieu Zimmer, Dong Li, Tianpei Yang, Jianye Hao, Wulong Liu
A survey on interpretable reinforcement learning. Mach. Learn. 113 (8) (2024)
Han Fang, Zhihao Song, Paul Weng, Yutong Ban
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer. CoRR (2024)
Jianshu Hu, Yunpeng Jiang, Paul Weng
Revisiting Data Augmentation in Deep Reinforcement Learning. ICLR (2024)
Guanbao Yu, Umer Siddique, Paul Weng
Fair Deep Reinforcement Learning with Generalized Gini Welfare Functions. AAMAS Workshops (2023)
Junqi Qian, Paul Weng, Chenmien Tan
Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learning. AAMAS (2023)
Guanbao Yu, Umer Siddique, Paul Weng
Fair Deep Reinforcement Learning with Preferential Treatment. ECAI (2023)
Timo Kaufmann, Paul Weng, Viktor Bengs, Eyke Hüllermeier
A Survey of Reinforcement Learning from Human Feedback. CoRR (2023)
Ruibin Bai, Xinan Chen, Zhi-Long Chen, Tianxiang Cui, Shuhui Gong, Wentao He, Xiaoping Jiang, Huan Jin, Jiahuan Jin, Graham Kendall, Jiawei Li, Zheng Lu, Jianfeng Ren, Paul Weng, Ning Xue, Huayan Zhang
Analytics and machine learning in vehicle routing research. Int. J. Prod. Res. 61 (1) (2023)
Thi Quynh Trang Vo, Mourad Baïou, Viet Hung Nguyen, Paul Weng
Improving Subtour Elimination Constraint Generation in Branch-and-Cut Algorithms for the TSP with Machine Learning. LION (2023)
Junqi Qian, Paul Weng, Chenmien Tan
Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learning. CoRR (2023)
Matthieu Zimmer, Xuening Feng, Claire Glanois, Zhaohui Jiang, Jianyi Zhang, Paul Weng, Dong Li, Jianye Hao, Wulong Liu
Differentiable Logic Machines. Trans. Mach. Learn. Res. 2023 (2023)
Zhaohui Jiang, Paul Weng
Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning. ECML/PKDD (4) (2023)
Chenmien Tan, Paul Weng
CVaR-Regret Bounds for Multi-armed Bandits. ACML (2022)
Hejun Lei, Paul Weng, Juan Rojas, Yisheng Guan
Planning with Q-Values in Sparse Reward Reinforcement Learning. ICIRA (1) (2022)
Claire Glanois, Zhaohui Jiang, Xuening Feng, Paul Weng, Matthieu Zimmer, Dong Li, Wulong Liu, Jianye Hao
Neuro-Symbolic Hierarchical Rule Induction. ICML (2022)
Jianshu Hu, Paul Weng
Solving Complex Manipulation Tasks with Model-Assisted Model-Free Reinforcement Learning. CoRL (2022)
Thi Quynh Trang Vo, Mourad Baïou, Viet Hung Nguyen, Paul Weng
A comparative study of linearization methods for Ordered Weighted Average. RNDM (2022)
Claire Glanois, Paul Weng, Matthieu Zimmer, Dong Li, Tianpei Yang, Jianye Hao, Wulong Liu
A Survey on Interpretable Reinforcement Learning. CoRR (2021)
Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng
Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning. ICML (2021)
Ruibin Bai, Xinan Chen, Zhi-Long Chen, Tianxiang Cui, Shuhui Gong, Wentao He, Xiaoping Jiang, Huan Jin, Jiahuan Jin, Graham Kendall, Jiawei Li, Zheng Lu, Jianfeng Ren, Paul Weng, Ning Xue, Huayan Zhang
Analytics and Machine Learning in Vehicle Routing Research. CoRR (2021)
Matthieu Zimmer, Xuening Feng, Claire Glanois, Zhaohui Jiang, Jianyi Zhang, Paul Weng, Jianye Hao, Dong Li, Wulong Liu
Differentiable Logic Machines. CoRR (2021)
Wenbin Ouyang, Yisen Wang, Shaochen Han, Zhejian Jin, Paul Weng
Improving Generalization of Deep Reinforcement Learning-based TSP Solvers. SSCI (2021)
Zhihao Ma, Yuzheng Zhuang, Paul Weng, Hankz Hankui Zhuo, Dong Li, Wulong Liu, Jianye Hao
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning. CoRR (2021)
Jiancong Huang, Juan Rojas, Matthieu Zimmer, Hongmin Wu, Yisheng Guan, Paul Weng
Hyperparameter Auto-Tuning in Self-Supervised Robotic Learning. IEEE Robotics Autom. Lett. 6 (2) (2021)
Jianyi Zhang, Paul Weng
Safe Distributional Reinforcement Learning. DAI (2021)
Jianyi Zhang, Paul Weng
Safe Distributional Reinforcement Learning. CoRR (2021)
Wenbin Ouyang, Yisen Wang, Shaochen Han, Zhejian Jin, Paul Weng
Improving Generalization of Deep Reinforcement Learning-based TSP Solvers. CoRR (2021)
Wenbin Ouyang, Yisen Wang, Paul Weng, Shaochen Han
Generalization in Deep RL for TSP Problems via Equivariance and Local Search. CoRR (2021)
Claire Glanois, Xuening Feng, Zhaohui Jiang, Paul Weng, Matthieu Zimmer, Dong Li, Wulong Liu
Neuro-Symbolic Hierarchical Rule Induction. CoRR (2021)
Matthieu Zimmer, Umer Siddique, Paul Weng
Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning. CoRR (2020)
Umer Siddique, Paul Weng, Matthieu Zimmer
Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewards. CoRR (2020)
Jiancong Huang, Juan Rojas, Matthieu Zimmer, Hongmin Wu, Yisheng Guan, Paul Weng
Hyperparameter Auto-tuning in Self-Supervised Robotic Learning. CoRR (2020)
Umer Siddique, Paul Weng, Matthieu Zimmer
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards. ICML (2020)
Olivier Buffer, Olivier Pietquin, Paul Weng
Reinforcement Learning. CoRR (2020)
Yinzhao Dong, Chao Yu, Paul Weng, Ahmed Maustafa, Hui Cheng, Hongwei Ge
Decomposed Deep Reinforcement Learning for Robotic Control. AAMAS (2020)
Yijiong Lin, Jiancong Huang, Matthieu Zimmer, Yisheng Guan, Juan Rojas, Paul Weng
Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning. IEEE Robotics Autom. Lett. 5 (4) (2020)
Paul Weng
Fairness in Reinforcement Learning. CoRR (2019)
Matthieu Zimmer, Paul Weng
An efficient reinforcement learning algorithm for learning deterministic policies in continuous domains. DAI (2019)
Yijiong Lin, Jiancong Huang, Matthieu Zimmer, Juan Rojas, Paul Weng
Invariant Transform Experience Replay. CoRR (2019)
Matthieu Zimmer, Paul Weng
Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains. CoRR (2019)
Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, Guihai Chen
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. CoRR (2019)
Matthieu Zimmer, Paul Weng
Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains. IJCAI (2019)
Qitian Wu, Yirui Gao, Xiaofeng Gao, Paul Weng, Guihai Chen
Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination. KDD (2019)
Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, Guihai Chen
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. WWW (2019)
Yijiong Lin, Jiancong Huang, Matthieu Zimmer, Juan Rojas, Paul Weng
Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation. CoRR (2019)
Qitian Wu, Chaoqi Yang, Hengrui Zhang, Xiaofeng Gao, Paul Weng, Guihai Chen
Adversarial Training Model Unifying Feature Driven and Point Process Perspectives for Event Popularity Prediction. CIKM (2018)
Marc T. Law, Paul Weng
Representing Relative Visual Attributes with a Reference-Point-Based Decision Model. ICPR (2018)
Emmanuel Hadoux, Aurélie Beynier, Nicolas Maudet, Paul Weng
Mediation of Debates with Dynamic Argumentative Behaviors. COMMA (2018)
M. Hadi Amini, Paul McNamara, Paul Weng, Orkun Karabasoglu, Yinliang Xu
Hierarchical Electric Vehicle Charging Aggregator Strategy Using Dantzig-Wolfe Decomposition. IEEE Des. Test 35 (6) (2018)
Viet Hung Nguyen, Paul Weng
An Efficient Primal-Dual Algorithm for Fair Combinatorial Optimization Problems. CoRR (2018)
Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Shie Mannor
Multi-objective Bandits: Optimizing the Generalized Gini Index. CoRR (2017)
Paul Weng, Olivier Spanjaard
Functional Reward Markov Decision Processes: Theory and Applications. Int. J. Artif. Intell. Tools 26 (3) (2017)
Dajian Li, Paul Weng, Orkun Karabasoglu
Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs. CoRR (2017)
Paul Weng, Zeqi Qiu, John A. W. B. Costanzo, Xiaoqi Yin, Bruno Sinopoli
Optimal Threshold Policies for Robust Data Center Control. CoRR (2017)
Hugo Gilbert, Paul Weng, Yan Xu
Optimizing Quantiles in Preference-Based Markov Decision Processes. AAAI (2017)
Paul Weng
From Preference-Based to Multiobjective Sequential Decision-Making. CoRR (2017)
Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Shie Mannor
Multi-objective Bandits: Optimizing the Generalized Gini Index. ICML (2017)
Viet Hung Nguyen, Paul Weng
An Efficient Primal-Dual Algorithm for Fair Combinatorial Optimization Problems. COCOA (1) (2017)
Paul Weng
From Preference-Based to Multiobjective Sequential Decision-Making. MIWAI (2016)
Hugo Gilbert, Paul Weng
Quantile Reinforcement Learning. CoRR (2016)
Hugo Gilbert, Bruno Zanuttini, Paul Weng, Paolo Viappiani, Esther Nicart
Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities. UAI (2016)
Dajian Li, Paul Weng, Orkun Karabasoglu
Finding Risk-Averse Shortest Path with Time-Dependent Stochastic Costs. MIWAI (2016)
Hugo Gilbert, Paul Weng, Yan Xu
Optimizing Quantiles in Preference-based Markov Decision Processes. CoRR (2016)
Emmanuel Hadoux, Aurélie Beynier, Nicolas Maudet, Paul Weng, Anthony Hunter
Optimization of Probabilistic Argumentation with Markov Decision Models. IJCAI (2015)
Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36 (1) (2015)
Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng
Reducing the Number of Queries in Interactive Value Iteration. ADT (2015)
Balázs Szörényi, Róbert Busa-Fekete, Paul Weng, Eyke Hüllermeier
Qualitative Multi-Armed Bandits: A Quantile-Based Approach. ICML (2015)
Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng
Solving MDPs with Skew Symmetric Bilinear Utility Functions. IJCAI (2015)
Darius Braziunas, Markus Endres, Kristen Brent Venable, Paul Weng, Lirong Xia
Preface. MPREF@AAAI (2014)
Emmanuel Hadoux, Aurélie Beynier, Paul Weng
Solving Hidden-Semi-Markov-Mode Markov Decision Problems. SUM (2014)
Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. Mach. Learn. 97 (3) (2014)
Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. CoRR (2013)
Paul Weng
Axiomatic Foundations of Generalized Qualitative Utility. MIWAI (2013)
Róbert Busa-Fekete, Balázs Szörényi, Weiwei Cheng, Paul Weng, Eyke Hüllermeier
Top-k Selection based on Adaptive Sampling of Noisy Preferences. ICML (3) (2013)
Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. AAAI (Late-Breaking Developments) (2013)
Paul Weng, Bruno Zanuttini
Interactive Value Iteration for Markov Decision Processes with Unknown Rewards. IJCAI (2013)
Olivier Spanjaard, Paul Weng
Markov Decision Processes with Functional Rewards. MIWAI (2013)
Wlodzimierz Ogryczak, Patrice Perny, Paul Weng
A Compromise Programming Approach to multiobjective Markov Decision Processes. Int. J. Inf. Technol. Decis. Mak. 12 (5) (2013)
Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna
Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. UAI (2013)
Wlodzimierz Ogryczak, Patrice Perny, Paul Weng
On WOWA Rank Reversal. MDAI (2012)
Paul Weng
Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility. CoRR (2012)
Paul Weng
Qualitative Decision Making Under Possibilistic Uncertainty: Toward more discriminating criteria CoRR (2012)
Paul Weng
Ordinal Decision Models for Markov Decision Processes. ECAI (2012)
Charles Delort, Olivier Spanjaard, Paul Weng
Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation. ADT (2011)
Wlodzimierz Ogryczak, Patrice Perny, Paul Weng
On Minimizing Ordered Weighted Regrets in Multiobjective Markov Decision Processes. ADT (2011)
Paul Weng
Markov Decision Processes with Ordinal Rewards: Reference Point-Based Preferences. ICAPS (2011)
Patrice Perny, Paul Weng
On Finding Compromise Solutions in Multiobjective Markov Decision Processes. ECAI (2010)
Paul Weng
Conditions générales pour l'admissibilité de la programmation dynamique dans la décision séquentielle possibiliste. Rev. d'Intelligence Artif. 21 (1) (2007)
Paul Weng
An Axiomatic Approach in Qualitative Decision Theory with Binary Possibilistic Utility. ECAI (2006)
Paul Weng
Processus de décision markoviens et préférences non classiques. Rev. d'Intelligence Artif. 20 (2-3) (2006)
Paul Weng
Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility. UAI (2006)
Patrice Perny, Olivier Spanjaard, Paul Weng
Algebraic Markov Decision Processes. IJCAI (2005)
Paul Weng
Qualitative Decision Making Under Possibilistic Uncertainty: Toward more Discriminating Criteria. UAI (2005)