Provable Multi-Party Reinforcement Learning with Diverse Human Feedback
Fuente:
arXiv
Saved in:
| Main Authors: | Zhong, Huiying, Deng, Zhun, Su, Weijie J., Wu, Zhiwei Steven, Zhang, Linjun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Recommending Best Paper Awards for ML/AI Conferences via the Isotonic Mechanism
by: Wen, Garrett G., et al.
Published: (2026)
by: Wen, Garrett G., et al.
Published: (2026)
Provable Offline Reinforcement Learning for Structured Cyclic MDPs
by: Lee, Kyungbok, et al.
Published: (2026)
by: Lee, Kyungbok, et al.
Published: (2026)
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
by: Zhang, Lujing, et al.
Published: (2024)
by: Zhang, Lujing, et al.
Published: (2024)
Tackling Copyright Issues in AI Image Generation Through Originality Estimation and Genericization
by: Chiba-Okabe, Hiroaki, et al.
Published: (2024)
by: Chiba-Okabe, Hiroaki, et al.
Published: (2024)
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
by: Lu, Miao, et al.
Published: (2022)
by: Lu, Miao, et al.
Published: (2022)
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
by: Lu, Haoran, et al.
Published: (2026)
by: Lu, Haoran, et al.
Published: (2026)
Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
by: Dong, Zihan, et al.
Published: (2026)
by: Dong, Zihan, et al.
Published: (2026)
What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning
by: Deng, Zhihong, et al.
Published: (2024)
by: Deng, Zhihong, et al.
Published: (2024)
Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles
by: Tang, Zhiwei, et al.
Published: (2023)
by: Tang, Zhiwei, et al.
Published: (2023)
Causal State Distillation for Explainable Reinforcement Learning
by: Lu, Wenhao, et al.
Published: (2023)
by: Lu, Wenhao, et al.
Published: (2023)
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning
by: Zhang, Jiaru, et al.
Published: (2025)
by: Zhang, Jiaru, et al.
Published: (2025)
Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
by: Fang, Luyang, et al.
Published: (2026)
by: Fang, Luyang, et al.
Published: (2026)
Peer Effect Estimation in the Presence of Simultaneous Feedback and Unobserved Confounders
by: Du, Xiaojing, et al.
Published: (2025)
by: Du, Xiaojing, et al.
Published: (2025)
Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection
by: Zhang, Jiarui, et al.
Published: (2024)
by: Zhang, Jiarui, et al.
Published: (2024)
Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes
by: Paul, Animesh Kumar, et al.
Published: (2025)
by: Paul, Animesh Kumar, et al.
Published: (2025)
End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
by: Zhou, Yidong, et al.
Published: (2025)
by: Zhou, Yidong, et al.
Published: (2025)
How Many Human Survey Respondents is a Large Language Model Worth? An Uncertainty Quantification Perspective
by: Huang, Chengpiao, et al.
Published: (2025)
by: Huang, Chengpiao, et al.
Published: (2025)
A Roadmap Towards Improving Multi-Agent Reinforcement Learning With Causal Discovery And Inference
by: Briglia, Giovanni, et al.
Published: (2025)
by: Briglia, Giovanni, et al.
Published: (2025)
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities
by: Lalou, Yanis, et al.
Published: (2024)
by: Lalou, Yanis, et al.
Published: (2024)
Causal Machine Learning for Surgical Interventions
by: Tamo, J. Ben, et al.
Published: (2025)
by: Tamo, J. Ben, et al.
Published: (2025)
Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning
by: Zhang, Zheyu, et al.
Published: (2025)
by: Zhang, Zheyu, et al.
Published: (2025)
Localized Conformal Multi-Quantile Regression
by: Lu, Yuan
Published: (2024)
by: Lu, Yuan
Published: (2024)
M$^3$TN: Multi-gate Mixture-of-Experts based Multi-valued Treatment Network for Uplift Modeling
by: Sun, Zexu, et al.
Published: (2024)
by: Sun, Zexu, et al.
Published: (2024)
DCRMTA: Unbiased Causal Representation for Multi-touch Attribution
by: Tang, Jiaming
Published: (2024)
by: Tang, Jiaming
Published: (2024)
Multi-Domain Causal Discovery in Bijective Causal Models
by: Jalaldoust, Kasra, et al.
Published: (2025)
by: Jalaldoust, Kasra, et al.
Published: (2025)
Generative Augmented Inference
by: Lu, Cheng, et al.
Published: (2026)
by: Lu, Cheng, et al.
Published: (2026)
An Economic Solution to Copyright Challenges of Generative AI
by: Wang, Jiachen T., et al.
Published: (2024)
by: Wang, Jiachen T., et al.
Published: (2024)
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery
by: Li, Xiaoxuan, et al.
Published: (2024)
by: Li, Xiaoxuan, et al.
Published: (2024)
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality
by: Li, Sai, et al.
Published: (2024)
by: Li, Sai, et al.
Published: (2024)
Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
by: Xiong, Guojun, et al.
Published: (2024)
by: Xiong, Guojun, et al.
Published: (2024)
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
by: Shen, ChengAo, et al.
Published: (2024)
by: Shen, ChengAo, et al.
Published: (2024)
Generally-Occurring Model Change for Robust Counterfactual Explanations
by: Xu, Ao, et al.
Published: (2024)
by: Xu, Ao, et al.
Published: (2024)
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series
by: Ma, Zhipeng, et al.
Published: (2024)
by: Ma, Zhipeng, et al.
Published: (2024)
Causal Temporal Regime Structure Learning
by: Rahmani, Abdellah, et al.
Published: (2023)
by: Rahmani, Abdellah, et al.
Published: (2023)
Distribution Matching for Self-Supervised Transfer Learning
by: Jiao, Yuling, et al.
Published: (2025)
by: Jiao, Yuling, et al.
Published: (2025)
Measure-Theoretic Anti-Causal Representation Learning
by: Behnam, Arman, et al.
Published: (2025)
by: Behnam, Arman, et al.
Published: (2025)
Rating Multi-Modal Time-Series Forecasting Models (MM-TSFM) for Robustness Through a Causal Lens
by: Lakkaraju, Kausik, et al.
Published: (2024)
by: Lakkaraju, Kausik, et al.
Published: (2024)
Statistical Tests for Replacing Human Decision Makers with Algorithms
by: Feng, Kai, et al.
Published: (2023)
by: Feng, Kai, et al.
Published: (2023)
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
by: Chen, Yang, et al.
Published: (2024)
by: Chen, Yang, et al.
Published: (2024)
Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)
by: Massidda, Riccardo, et al.
Published: (2024)
Similar Items
-
Recommending Best Paper Awards for ML/AI Conferences via the Isotonic Mechanism
by: Wen, Garrett G., et al.
Published: (2026) -
Provable Offline Reinforcement Learning for Structured Cyclic MDPs
by: Lee, Kyungbok, et al.
Published: (2026) -
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
by: Zhang, Lujing, et al.
Published: (2024) -
Tackling Copyright Issues in AI Image Generation Through Originality Estimation and Genericization
by: Chiba-Okabe, Hiroaki, et al.
Published: (2024) -
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
by: Lu, Miao, et al.
Published: (2022)