Cover Image

Towards Understanding Generalization and Stability Gaps between Centralized and Decentralized Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Yan, Shen, Li, Tao, Dacheng
Format:	Preprint
Published:	2023
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

Stability and Generalization for Distributed SGDA
by: Zhu, Miaoxi, et al.
Published: (2024)

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

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
by: Sun, Yan, et al.
Published: (2023)

A Unified Analysis for Finite Weight Averaging
by: Wang, Peng, et al.
Published: (2024)

Decentralized Directed Collaboration for Personalized Federated Learning
by: Liu, Yingqi, et al.
Published: (2024)

The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity
by: Wu, Tongle, et al.
Published: (2024)

Multinoulli Extension: A Lossless Continuous Relaxation for Partition-Constrained Subset Selection
by: Zhang, Qixin, et al.
Published: (2026)

Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
by: Zhang, Qixin, et al.
Published: (2025)

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

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
by: Zhang, Qixin, et al.
Published: (2025)

Sporadic Gradient Tracking over Directed Graphs: A Theoretical Perspective on Decentralized Federated Learning
by: Zehtabi, Shahryar, 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)

Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
by: Pan, Xiaokang, et al.
Published: (2024)

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

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

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

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

Towards Fast Rates for Federated and Multi-Task Reinforcement Learning
by: Zhu, Feng, et al.
Published: (2024)

Stabilized Proximal-Point Methods for Federated Optimization
by: Jiang, Xiaowen, et al.
Published: (2024)

Decentralized Multi-Task Online Convex Optimization Under Random Link Failures
by: Yan, Wenjing, et al.
Published: (2024)

Understanding Optimization in Deep Learning with Central Flows
by: Cohen, Jeremy M., et al.
Published: (2024)

Learning Aligned Stability in Neural ODEs Reconciling Accuracy with Robustness
by: Luo, Chaoyang, et al.
Published: (2025)

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)

Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum
by: Zhou, Yuan, et al.
Published: (2025)

Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization
by: Liu, Wei, et al.
Published: (2025)

The Convergence of Dynamic Routing between Capsules
by: Ye, Daoyuan, et al.
Published: (2025)

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

Decentralized Personalized Federated Learning for Min-Max Problems
by: Borodich, Ekaterina, 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 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)

SGD at the Edge of Stability: The Stochastic Sharpness Gap
by: Liao, Fangshuo, et al.
Published: (2026)

FedGiA: An Efficient Hybrid Algorithm for Federated Learning
by: Zhou, Shenglong, et al.
Published: (2022)

Quantum Learning and Estimation for Coordinated Operation between Distribution Networks and Energy Communities
by: Zhuang, Yingrui, et al.
Published: (2025)

Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
by: Wiltzer, Harley, et al.
Published: (2024)

Towards Faster Decentralized Stochastic Optimization with Communication Compression
by: Islamov, Rustem, et al.
Published: (2024)

Locally Adaptive Federated Learning
by: Mukherjee, Sohom, et al.
Published: (2023)