Buchumschlag

Distributed TD Tracking with Linear Function Approximation over Directed Communication Networks

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Yang, Haocheng, Zhao, Shengchao, Liu, Yongchao
Format:	Preprint
Veröffentlicht:	2026
Schlagworte:	Optimization and Control
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Efficient Gradient Tracking Algorithms for Distributed Optimization Problems with Inexact Communication
von: Zhao, Shengchao, et al.
Veröffentlicht: (2025)

A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation
von: Mitra, Aritra
Veröffentlicht: (2024)

A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
von: Lee, Wei-Cheng, et al.
Veröffentlicht: (2025)

SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
von: Mangold, Paul, et al.
Veröffentlicht: (2024)

ADMM-Tracking Gradient for Distributed Optimization over Asynchronous and Unreliable Networks
von: Carnevale, Guido, et al.
Veröffentlicht: (2023)

The Barzilai-Borwein Method for Distributed Optimization over Unbalanced Directed Networks
von: Hu, Jinhui, et al.
Veröffentlicht: (2023)

Learning POMDPs with Linear Function Approximation and Finite Memory
von: Kara, Ali Devran
Veröffentlicht: (2025)

Learning with Linear Function Approximations in Mean-Field Control
von: Bayraktar, Erhan, et al.
Veröffentlicht: (2024)

Direct Data-Driven Linear Quadratic Tracking via Policy Optimization
von: Kang, Shubo, et al.
Veröffentlicht: (2026)

Approximate Solution Methods for the Average Reward Criterion in Optimal Tracking Control of Linear Systems
von: Nguyen, Duc Cuong
Veröffentlicht: (2025)

On the Resolution of Stochastic MPECs over Networks: Distributed Implicit Zeroth-Order Gradient Tracking Methods
von: Ebrahimi, Mohammadjavad, et al.
Veröffentlicht: (2025)

Linear Convergence of Data-Enabled Policy Optimization for Linear Quadratic Tracking
von: Kang, Shubo, et al.
Veröffentlicht: (2024)

On Linear Convergence of Distributed Stochastic Bilevel Optimization over Undirected Networks via Gradient Aggregation
von: Tak, Ajay, et al.
Veröffentlicht: (2025)

Distributed Priority-Based Load Shedding over Time-Varying Communication Networks
von: Aghajan, Adel, et al.
Veröffentlicht: (2024)

Accelerated Alternating Direction Method of Multipliers Gradient Tracking for Distributed Optimization
von: Sebastián, Eduardo, et al.
Veröffentlicht: (2024)

Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks
von: Nguyen, Duong Thuy Anh, et al.
Veröffentlicht: (2024)

Generic Frameworks for Distributed Functional Optimization and Learning over Time-Varying Networks
von: Yu, Zhan, et al.
Veröffentlicht: (2025)

Stochastic Momentum Tracking Push-Pull for Decentralized Optimization over Directed Graphs
von: Fan, Wenqi, et al.
Veröffentlicht: (2026)

(Corrected Version) Push-LSVRG-UP: Distributed Stochastic Optimization over Unbalanced Directed Networks with Uncoordinated Triggered Probabilities
von: Hu, Jinhui, et al.
Veröffentlicht: (2023)

Anderson Acceleration for Distributed Constrained Optimization over Time-varying Networks
von: Liu, Haijuan, et al.
Veröffentlicht: (2026)

Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
von: Cayci, Semih, et al.
Veröffentlicht: (2021)

Online Tracking with Predictions for Nonlinear Systems with Koopman Linear Embedding
von: Pai, Chih-Fan, et al.
Veröffentlicht: (2026)

Cryptography-Based Privacy-Preserving Method for Distributed Optimization over Time-Varying Directed Graphs with Enhanced Efficiency
von: Liu, Bing, et al.
Veröffentlicht: (2024)

Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency
von: Cai, Qi, et al.
Veröffentlicht: (2022)

Optimal Adaptive Control of Linear Stochastic Systems with Quadratic Cost Function
von: Liu, Nian, et al.
Veröffentlicht: (2024)

Two-Stage Distributionally Robust Conic Linear Programming over 1-Wasserstein Balls
von: Byeon, Geunyeong, et al.
Veröffentlicht: (2022)

Distributed Riemannian Stochastic Gradient Tracking Algorithm on the Stiefel Manifold
von: Zhao, Jishu, et al.
Veröffentlicht: (2024)

Strengthened and Faster Linear Approximation to Joint Chance Constraints with Wasserstein Ambiguity
von: Zhou, Yihong, et al.
Veröffentlicht: (2024)

Compressed Gradient Tracking Algorithms for Distributed Nonconvex Optimization
von: Xu, Lei, et al.
Veröffentlicht: (2023)

Distributed Nash Equilibrium Seeking in Aggregative Games over Jointly Connected and Weight-Balanced Networks
von: Liu, Zhaocong, et al.
Veröffentlicht: (2024)

Approximate Solutions in Linear Fractional Vector Optimization
von: Huong, Nguyen Thi Thu
Veröffentlicht: (2024)

Fast Consensus over Almost Regular Directed Graphs
von: Lu, Susie, et al.
Veröffentlicht: (2025)

Distributionally Robust Model Order Reduction for Linear Systems
von: Liu, Le, et al.
Veröffentlicht: (2025)

Mixed-Integer Linear Programming Approximations for the Stochastic Knapsack
von: Rossi, Roberto, et al.
Veröffentlicht: (2025)

Riemannian Momentum Tracking: Distributed Optimization with Momentum on Compact Submanifolds
von: Chen, Jun, et al.
Veröffentlicht: (2026)

Optimality of Linear Policies for Distributionally Robust Linear Quadratic Gaussian Regulator with Stationary Distributions
von: Lanzetti, Nicolas, et al.
Veröffentlicht: (2024)

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity
von: Wang, Han, et al.
Veröffentlicht: (2023)

Optimality of Linear Policies in Distributionally Robust Linear Quadratic Control
von: Taşkesen, Bahar, et al.
Veröffentlicht: (2025)

Smoothing Gradient Tracking for Decentralized Optimization over the Stiefel Manifold with Non-smooth Regularizers
von: Wang, Lei, et al.
Veröffentlicht: (2023)

Co-Optimizing Distributed Energy Resources in Linear Complexity under Net Energy Metering
von: Alahmed, Ahmed S., et al.
Veröffentlicht: (2022)