:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chen, Tianyi, Ma, Haitong, Li, Na, Wang, Kai, Dai, Bo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2507.23675
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Online Reinforcement Learning for Diffusion Policy
by: Ma, Haitong, et al.
Published: (2025)

Stochastic MeanFlow Policies: One-Step Generative Control with Entropic Mirror Descent
by: Wang, Zeyuan, et al.
Published: (2026)

Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint
by: Ma, Haitong, et al.
Published: (2024)

Efficient Duple Perturbation Robustness in Low-rank MDPs
by: Hu, Yang, et al.
Published: (2024)

Offline Imitation Learning upon Arbitrary Demonstrations by Pre-Training Dynamics Representations
by: Ma, Haitong, et al.
Published: (2025)

Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
by: Ren, Zhaolin, et al.
Published: (2023)

Flow Matching Policy Optimization with Mirror Descent and Entropy Constraints
by: Gao, Ting, et al.
Published: (2026)

Policy Mirror Descent with Lookahead
by: Protopapas, Kimon, et al.
Published: (2024)

On the Effect of Regularization in Policy Mirror Descent
by: Kleuker, Jan Felix, et al.
Published: (2025)

FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies
by: Gao, Chenxiao, et al.
Published: (2026)

On the Convergence of Policy in Unregularized Policy Mirror Descent
by: Lin, Dachao, et al.
Published: (2022)

Functional Acceleration for Policy Mirror Descent
by: Chelu, Veronica, et al.
Published: (2024)

Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds
by: Xu, Zhenghao, et al.
Published: (2023)

On the Convergence of Policy Mirror Descent with Temporal Difference Evaluation
by: Liu, Jiacai, et al.
Published: (2025)

Primal-Dual Spectral Representation for Off-policy Evaluation
by: Hu, Yang, et al.
Published: (2024)

Never Saddle for Reparameterized Steepest Descent as Mirror Flow
by: Jacobs, Tom, et al.
Published: (2026)

Beyond State-Wise Mirror Descent: Offline Policy Optimization with Parametric Policies
by: Li, Xiang, et al.
Published: (2026)

Path-Space Mirror Descent for On-Policy Reinforcement Learning under the Generalized Schrödinger Bridge
by: Gong, Yuehu, et al.
Published: (2026)

Latent Policy Steering through One-Step Flow Policies
by: Im, Hokyun, et al.
Published: (2026)

Truncated Rectified Flow Policy for Reinforcement Learning with One-Step Sampling
by: Zhou, Xubin, et al.
Published: (2026)

A Mirror Descent Perspective of Smoothed Sign Descent
by: Wang, Shuyang, et al.
Published: (2024)

One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow
by: Wang, Zeyuan, et al.
Published: (2025)

Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
by: Sherman, Uri, et al.
Published: (2025)

StaQ it! Growing neural networks for Policy Mirror Descent
by: Shilova, Alena, et al.
Published: (2025)

Distributed Thompson sampling under constrained communication
by: Zerefa, Saba, et al.
Published: (2024)

Policy Mirror Descent with Temporal Difference Learning: Sample Complexity under Online Markov Data
by: Li, Wenye, et al.
Published: (2025)

Parameter-free Mirror Descent
by: Jacobsen, Andrew, et al.
Published: (2022)

Mirror Descent on Riemannian Manifolds
by: Jiang, Jiaxin, et al.
Published: (2026)

Mirror Descent Policy Optimisation for Robust Constrained Markov Decision Processes
by: Bossens, David M., et al.
Published: (2025)

Trajectory Consistency for One-Step Generation on Euler Mean Flows
by: Li, Zhiqi, et al.
Published: (2026)

Configurable Mirror Descent: Towards a Unification of Decision Making
by: Li, Pengdeng, et al.
Published: (2024)

The Hidden Cost of Approximation in Online Mirror Descent
by: Schlisselberg, Ofir, et al.
Published: (2025)

Max-Entropy Reinforcement Learning with Flow Matching and A Case Study on LQR
by: Zhang, Yuyang, et al.
Published: (2025)

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
by: Alfano, Carlo, et al.
Published: (2023)

Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent
by: Xu, Hang, et al.
Published: (2024)

Value Mirror Descent for Reinforcement Learning
by: Jia, Zhichao, et al.
Published: (2026)

A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent
by: Wang, Shuche, et al.
Published: (2024)

Approximation of Log-Partition Function in Policy Mirror Descent Induces Implicit Regularization for LLM Post-Training
by: Xu, Zhenghao, et al.
Published: (2026)

Reference-Sampled Boltzmann Projection for KL-Regularized RLVR: Target-Matched Weighted SFT, Finite One-Shot Gaps, and Policy Mirror Descent
by: Shu, Yao, et al.
Published: (2026)

Learnable Loss Geometries with Mirror Descent for Scalable and Convergent Meta-Learning
by: Zhang, Yilang, et al.
Published: (2025)