Near-Optimal Primal-Dual Algorithm for Learning Linear Mixture CMDPs with Adversarial Rewards
Fuente:
arXiv
Saved in:
| Main Authors: | Yu, Kihyun, Bae, Seoungbin, Lee, Dabeen |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Primal-Dual Policy Optimization for Linear CMDPs with Adversarial Losses
by: Yu, Kihyun, et al.
Published: (2026)
by: Yu, Kihyun, et al.
Published: (2026)
Learning Weakly Communicating Average-Reward CMDPs: Strong Duality and Improved Regret
by: Yu, Kihyun, et al.
Published: (2026)
by: Yu, Kihyun, et al.
Published: (2026)
Improved Regret Bound for Safe Reinforcement Learning via Tighter Cost Pessimism and Reward Optimism
by: Yu, Kihyun, et al.
Published: (2024)
by: Yu, Kihyun, et al.
Published: (2024)
Chebyshev Center-Based Direction Selection for Multi-Objective Optimization and Training PINNs
by: Yoon, Hoyeol, et al.
Published: (2026)
by: Yoon, Hoyeol, et al.
Published: (2026)
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
by: Chae, Woojin, et al.
Published: (2024)
by: Chae, Woojin, et al.
Published: (2024)
Nearly Optimal Linear Convergence of Stochastic Primal-Dual Methods for Linear Programming
by: Lu, Haihao, et al.
Published: (2021)
by: Lu, Haihao, et al.
Published: (2021)
Provably Efficient Infinite-Horizon Average-Reward Reinforcement Learning with Linear Function Approximation
by: Chae, Woojin, et al.
Published: (2024)
by: Chae, Woojin, et al.
Published: (2024)
Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
by: Huang, Ruichuan, et al.
Published: (2025)
by: Huang, Ruichuan, et al.
Published: (2025)
Stochastic-Constrained Stochastic Optimization with Markovian Data
by: Kim, Yeongjong, et al.
Published: (2023)
by: Kim, Yeongjong, et al.
Published: (2023)
Logistic Bandits with $\tilde{O}(\sqrt{dT})$ Regret without Context Diversity Assumptions
by: Bae, Seoungbin, et al.
Published: (2026)
by: Bae, Seoungbin, et al.
Published: (2026)
Neural Logistic Bandits
by: Bae, Seoungbin, et al.
Published: (2025)
by: Bae, Seoungbin, et al.
Published: (2025)
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
by: Zhang, Junkai, et al.
Published: (2023)
by: Zhang, Junkai, et al.
Published: (2023)
Infinite-Horizon Reinforcement Learning with Multinomial Logistic Function Approximation
by: Park, Jaehyun, et al.
Published: (2024)
by: Park, Jaehyun, et al.
Published: (2024)
Parameter-Free Algorithms for Performative Regret Minimization under Decision-Dependent Distributions
by: Park, Sungwoo, et al.
Published: (2024)
by: Park, Sungwoo, et al.
Published: (2024)
Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits
by: Bae, Seoungbin, et al.
Published: (2026)
by: Bae, Seoungbin, et al.
Published: (2026)
Policy-based Primal-Dual Methods for Concave CMDP with Variance Reduction
by: Ying, Donghao, et al.
Published: (2022)
by: Ying, Donghao, et al.
Published: (2022)
Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning
by: Li, Zihao, et al.
Published: (2024)
by: Li, Zihao, et al.
Published: (2024)
An Adaptively Inexact Method for Bilevel Learning Using Primal-Dual Style Differentiation
by: Bogensperger, Lea, et al.
Published: (2024)
by: Bogensperger, Lea, et al.
Published: (2024)
A Two-Timescale Primal-Dual Framework for Reinforcement Learning via Online Dual Variable Guidance
by: Wolter, Axel Friedrich, et al.
Published: (2025)
by: Wolter, Axel Friedrich, et al.
Published: (2025)
Constrained Sampling with Primal-Dual Langevin Monte Carlo
by: Chamon, Luiz F. O., et al.
Published: (2024)
by: Chamon, Luiz F. O., et al.
Published: (2024)
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
by: Zeng, Sihan, et al.
Published: (2021)
by: Zeng, Sihan, et al.
Published: (2021)
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2023)
by: Ding, Dongsheng, et al.
Published: (2023)
Online Inference of Constrained Optimization: Primal-Dual Optimality and Sequential Quadratic Programming
by: Gao, Yihang, et al.
Published: (2025)
by: Gao, Yihang, et al.
Published: (2025)
Queue Length Regret Bounds for Contextual Queueing Bandits
by: Bae, Seoungbin, et al.
Published: (2026)
by: Bae, Seoungbin, et al.
Published: (2026)
Adaptive Primal-Dual Method for Safe Reinforcement Learning
by: Chen, Weiqin, et al.
Published: (2024)
by: Chen, Weiqin, et al.
Published: (2024)
Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
by: Sinha, Abhishek, et al.
Published: (2023)
by: Sinha, Abhishek, et al.
Published: (2023)
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
by: Zhao, Heyang, et al.
Published: (2023)
by: Zhao, Heyang, et al.
Published: (2023)
Multi-Timescale Primal Dual Hybrid Gradient with Application to Distributed Optimization
by: Zhang, Junhui, et al.
Published: (2025)
by: Zhang, Junhui, et al.
Published: (2025)
Some Primal-Dual Theory for Subgradient Methods for Strongly Convex Optimization
by: Grimmer, Benjamin, et al.
Published: (2023)
by: Grimmer, Benjamin, et al.
Published: (2023)
Near-optimal and Efficient First-Order Algorithm for Multi-Task Learning with Shared Linear Representation
by: Ding, Shihong, et al.
Published: (2026)
by: Ding, Shihong, et al.
Published: (2026)
Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
by: Soma, Tasuku, et al.
Published: (2022)
by: Soma, Tasuku, et al.
Published: (2022)
Scalable Approximate Algorithms for Optimal Transport Linear Models
by: Kacprzak, Tomasz, et al.
Published: (2025)
by: Kacprzak, Tomasz, et al.
Published: (2025)
Scalable Min-Max Optimization via Primal-Dual Exact Pareto Optimization
by: Park, Sangwoo, et al.
Published: (2025)
by: Park, Sangwoo, et al.
Published: (2025)
A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
by: Jiang, Liuyuan, et al.
Published: (2024)
by: Jiang, Liuyuan, et al.
Published: (2024)
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
by: Mehta, Ronak, et al.
Published: (2024)
by: Mehta, Ronak, et al.
Published: (2024)
Reward-Relevance-Filtered Linear Offline Reinforcement Learning
by: Zhou, Angela
Published: (2024)
by: Zhou, Angela
Published: (2024)
Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators
by: Han, Yinbin, et al.
Published: (2023)
by: Han, Yinbin, et al.
Published: (2023)
Offline-Online Reinforcement Learning for Linear Mixture MDPs
by: Zhang, Zhongjun, et al.
Published: (2026)
by: Zhang, Zhongjun, et al.
Published: (2026)
Nonsmooth Nonconvex-Nonconcave Minimax Optimization: Primal-Dual Balancing and Iteration Complexity Analysis
by: Li, Jiajin, et al.
Published: (2022)
by: Li, Jiajin, et al.
Published: (2022)
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
by: Zhu, Shuchen, et al.
Published: (2024)
by: Zhu, Shuchen, et al.
Published: (2024)
Similar Items
-
Primal-Dual Policy Optimization for Linear CMDPs with Adversarial Losses
by: Yu, Kihyun, et al.
Published: (2026) -
Learning Weakly Communicating Average-Reward CMDPs: Strong Duality and Improved Regret
by: Yu, Kihyun, et al.
Published: (2026) -
Improved Regret Bound for Safe Reinforcement Learning via Tighter Cost Pessimism and Reward Optimism
by: Yu, Kihyun, et al.
Published: (2024) -
Chebyshev Center-Based Direction Selection for Multi-Objective Optimization and Training PINNs
by: Yoon, Hoyeol, et al.
Published: (2026) -
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
by: Chae, Woojin, et al.
Published: (2024)