Cover Image

The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Tongle, Li, Zhize, Sun, Ying
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness
by: Patel, Kumar Kshitij
Published: (2025)

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data
by: Zhu, Shuchen, et al.
Published: (2026)

EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback
by: Fatkhullin, Ilyas, et al.
Published: (2021)

Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance
by: Chen, Hongxu, et al.
Published: (2026)

Towards Understanding Generalization and Stability Gaps between Centralized and Decentralized Federated Learning
by: Sun, Yan, et al.
Published: (2023)

Convergence of Distributed Adaptive Optimization with Local Updates
by: Cheng, Ziheng, et al.
Published: (2024)

Accelerating Decentralized Optimization via Overlapping Local Steps
by: Zhou, Yijie, et al.
Published: (2026)

Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach
by: Nguyen, Hoang Huy, et al.
Published: (2024)

Decentralized Stochastic Nonconvex Optimization under the Relaxed Smoothness
by: Luo, Luo, et al.
Published: (2025)

Scalable Decentralized Learning with Teleportation
by: Takezawa, Yuki, et al.
Published: (2025)

Problem-Parameter-Free Decentralized Bilevel Optimization
by: Zhai, Zhiwei, et al.
Published: (2025)

Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
by: Wang, Xiaolu, et al.
Published: (2024)

Learning-Augmented Decentralized Online Convex Optimization in Networks
by: Li, Pengfei, et al.
Published: (2023)

Enhancing Convergence of Decentralized Gradient Tracking under the KL Property
by: Chen, Xiaokai, et al.
Published: (2024)

Faster Adaptive Decentralized Learning Algorithms
by: Huang, Feihu, et al.
Published: (2024)

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

Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data
by: Liu, Jie, et al.
Published: (2025)

Stability and Generalization of Push-Sum Based Decentralized Optimization over Directed Graphs
by: Liang, Yifei, et al.
Published: (2026)

Provably Convergent Decentralized Optimization over Directed Graphs under Generalized Smoothness
by: Bo, Yanan, et al.
Published: (2026)

Adam Converges Without Any Modification On Update Rules
by: Zhang, Yushun, et al.
Published: (2026)

Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Data
by: Qiu, Pu, et al.
Published: (2026)

Asynchronous Decentralized SGD under Non-Convexity: A Block-Coordinate Descent Framework
by: Zhou, Yijie, et al.
Published: (2025)

The Role of Target Update Frequencies in Q-Learning
by: Weissmann, Simon, et al.
Published: (2026)

Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
by: Ye, Lintao, et al.
Published: (2022)

Retraction-Free Decentralized Non-convex Optimization with Orthogonal Constraints
by: Sun, Youbang, et al.
Published: (2024)

RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent
by: Fang, Cheng, et al.
Published: (2025)

Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
by: Zhang, Siqi, et al.
Published: (2023)

Decentralized Sparse Linear Regression via Gradient-Tracking: Linear Convergence and Statistical Guarantees
by: Maros, Marie, et al.
Published: (2022)

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

X-VFL: A New Vertical Federated Learning Framework with Cross Completion and Decision Subspace Alignment
by: Yao, Qinghua, et al.
Published: (2025)

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

Less is More: Convergence Benefits of Fewer Data Weight Updates over Longer Horizon
by: Das, Rudrajit, et al.
Published: (2026)

Decentralized Sum-of-Nonconvex Optimization
by: Liu, Zhuanghua, et al.
Published: (2024)

Decentralized and Equitable Optimal Transport
by: Lau, Ivan, et al.
Published: (2024)

Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
by: Li, Huan, et al.
Published: (2021)

Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
by: Ahn, Kwangjun, et al.
Published: (2024)

Decentralized Contextual Bandits with Network Adaptivity
by: Deng, Chuyun, et al.
Published: (2025)

Heavy-Tail Phenomenon in Decentralized SGD
by: Gurbuzbalaban, Mert, et al.
Published: (2022)

Optimal Local Convergence Rates of Stochastic First-Order Methods under Local $α$-PL
by: Masiha, Saeed, et al.
Published: (2024)

Risk-sensitive Markov Decision Process and Learning under General Utility Functions
by: Wu, Zhengqi, et al.
Published: (2023)