Image de couverture de livre

Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Li, Jiaxiang, Chen, Xuxing, Ma, Shiqian, Hong, Mingyi
Format:	Preprint
Publié:	2024
Sujets:	Optimization and Control Distributed, Parallel, and Cluster Computing
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Decentralized Nonsmooth Nonconvex Optimization with Client Sampling
par: Chen, Xinyan, et autres
Publié: (2026)

Decentralized Nonconvex Optimization under Heavy-Tailed Noise: Normalization and Optimal Convergence
par: Yu, Shuhua, et autres
Publié: (2025)

Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization
par: Lin, Zhenwei, et autres
Publié: (2023)

A Single-Loop Algorithm for Decentralized Bilevel Optimization
par: Dong, Youran, et autres
Publié: (2023)

Decentralized Distributed Optimization for Saddle Point Problems
par: Rogozin, Alexander, et autres
Publié: (2021)

S$^3$LDBO: A Snapshot Single-Loop Algorithm for Decentralized Bilevel Optimization
par: Yin, Chao, et autres
Publié: (2026)

Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum
par: Zhou, Yuan, et autres
Publié: (2025)

A Stochastic Approximation Approach for Efficient Decentralized Optimization on Random Networks
par: Yau, Chung-Yiu, et autres
Publié: (2024)

Smoothed Gradient Clipping and Error Feedback for Decentralized Optimization under Symmetric Heavy-Tailed Noise
par: Yu, Shuhua, et autres
Publié: (2023)

Optimality in Decentralized Optimization under Bandwidth Constraints
par: Tyurin, Alexander
Publié: (2026)

Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization
par: Qin, Zhen, et autres
Publié: (2023)

A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration
par: Hu, Yuchen, et autres
Publié: (2025)

From Sequential to Parallel: Reformulating Dynamic Programming as GPU Kernels for Large-Scale Stochastic Combinatorial Optimization
par: Zhao, Jingyi, et autres
Publié: (2026)

Decentralized Personalized Federated Learning for Min-Max Problems
par: Borodich, Ekaterina, et autres
Publié: (2021)

An Optimistic Gradient Tracking Method for Distributed Minimax Optimization
par: Huang, Yan, et autres
Publié: (2025)

Distributed Stochastic Momentum Tracking with Local Updates: Achieving Optimal Communication and Iteration Complexities
par: Huang, Kun, et autres
Publié: (2025)

Communication-Efficient Federated Optimization over Semi-Decentralized Networks
par: Wang, He, et autres
Publié: (2023)

A First-Order Algorithm for Decentralised Min-Max Problems
par: Malitsky, Yura, et autres
Publié: (2023)

A Double Tracking Method for Optimization with Decentralized Generalized Orthogonality Constraints
par: Wang, Lei, et autres
Publié: (2024)

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
par: He, Yutong, et autres
Publié: (2023)

Tailoring Gradient Methods for Differentially-Private Distributed Optimization
par: Wang, Yongqiang, et autres
Publié: (2022)

Correlated Quantization for Faster Nonconvex Distributed Optimization
par: Panferov, Andrei, et autres
Publié: (2024)

Distributed Constraint-Coupled Optimization: Harnessing ADMM-consensus for robustness
par: Messilem, Mohamed Abdelmouamin, et autres
Publié: (2025)

Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks
par: Heydaribeni, Nasimeh, et autres
Publié: (2023)

Decentralized Directed Collaboration for Personalized Federated Learning
par: Liu, Yingqi, et autres
Publié: (2024)

One-Point Feedback for Composite Optimization with Applications to Distributed and Federated Learning
par: Beznosikov, Aleksandr, et autres
Publié: (2021)

Optimizing Stochastic Gradient Push under Broadcast Communications
par: Nguyen, Tuan, et autres
Publié: (2026)

Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems
par: Li, Junyi, et autres
Publié: (2023)

Energy-efficient Decentralized Learning via Graph Sparsification
par: Zhang, Xusheng, et autres
Publié: (2024)

Stochastic Controlled Averaging for Federated Learning with Communication Compression
par: Huang, Xinmeng, et autres
Publié: (2023)

Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity
par: Bylinkin, Dmitry, et autres
Publié: (2024)

Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction
par: Tovmasyan, Zhirayr, et autres
Publié: (2026)

D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems
par: Li, Hongpei, et autres
Publié: (2026)

A Hybrid Stochastic Gradient Tracking Method for Distributed Online Optimization Over Time-Varying Directed Networks
par: Shi, Xinli, et autres
Publié: (2025)

Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
par: Zehtabi, Shahryar, et autres
Publié: (2022)

A Penalty-Based Method for Communication-Efficient Decentralized Bilevel Programming
par: Nazari, Parvin, et autres
Publié: (2022)

A GPU-Accelerated Hybrid Method for a Class of Multi-Depot Vehicle Routing Problems
par: Lei, Zhenyu, et autres
Publié: (2026)

CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
par: Huang, Kun, et autres
Publié: (2023)

Time-varying Mixing Matrix Design for Energy-efficient Decentralized Federated Learning
par: Zhang, Xusheng, et autres
Publié: (2025)

dHPR: A Distributed Halpern Peaceman--Rachford Method for Non-smooth Distributed Optimization Problems
par: Feng, Zhangcheng, et autres
Publié: (2025)