Saved in:
| Main Authors: | Hu, Yuchen, Chen, Xi, Liu, Weidong, Mao, Xiaojun |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.19082 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum
by: Zhou, Yuan, et al.
Published: (2025)
by: Zhou, Yuan, et al.
Published: (2025)
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
by: He, Yutong, et al.
Published: (2023)
by: He, Yutong, et al.
Published: (2023)
A Stochastic Approximation Approach for Efficient Decentralized Optimization on Random Networks
by: Yau, Chung-Yiu, et al.
Published: (2024)
by: Yau, Chung-Yiu, et al.
Published: (2024)
A Single-Loop Algorithm for Decentralized Bilevel Optimization
by: Dong, Youran, et al.
Published: (2023)
by: Dong, Youran, et al.
Published: (2023)
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
by: Huang, Kun, et al.
Published: (2023)
by: Huang, Kun, et al.
Published: (2023)
An Accelerated Distributed Stochastic Gradient Method with Momentum
by: Huang, Kun, et al.
Published: (2024)
by: Huang, Kun, et al.
Published: (2024)
S$^3$LDBO: A Snapshot Single-Loop Algorithm for Decentralized Bilevel Optimization
by: Yin, Chao, et al.
Published: (2026)
by: Yin, Chao, et al.
Published: (2026)
Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction
by: Tovmasyan, Zhirayr, et al.
Published: (2026)
by: Tovmasyan, Zhirayr, et al.
Published: (2026)
Optimizing Stochastic Gradient Push under Broadcast Communications
by: Nguyen, Tuan, et al.
Published: (2026)
by: Nguyen, Tuan, et al.
Published: (2026)
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity
by: Maranjyan, Artavazd, et al.
Published: (2022)
by: Maranjyan, Artavazd, et al.
Published: (2022)
A Double Tracking Method for Optimization with Decentralized Generalized Orthogonality Constraints
by: Wang, Lei, et al.
Published: (2024)
by: Wang, Lei, et al.
Published: (2024)
A Hybrid Stochastic Gradient Tracking Method for Distributed Online Optimization Over Time-Varying Directed Networks
by: Shi, Xinli, et al.
Published: (2025)
by: Shi, Xinli, et al.
Published: (2025)
Decentralized Directed Collaboration for Personalized Federated Learning
by: Liu, Yingqi, et al.
Published: (2024)
by: Liu, Yingqi, et al.
Published: (2024)
Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method
by: Sadiev, Abdurakhmon, et al.
Published: (2026)
by: Sadiev, Abdurakhmon, et al.
Published: (2026)
Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization
by: Lin, Zhenwei, et al.
Published: (2023)
by: Lin, Zhenwei, et al.
Published: (2023)
A Penalty-Based Method for Communication-Efficient Decentralized Bilevel Programming
by: Nazari, Parvin, et al.
Published: (2022)
by: Nazari, Parvin, et al.
Published: (2022)
Decentralized Personalized Federated Learning for Min-Max Problems
by: Borodich, Ekaterina, et al.
Published: (2021)
by: Borodich, Ekaterina, et al.
Published: (2021)
Energy-efficient Decentralized Learning via Graph Sparsification
by: Zhang, Xusheng, et al.
Published: (2024)
by: Zhang, Xusheng, et al.
Published: (2024)
Communication-Efficient Federated Optimization over Semi-Decentralized Networks
by: Wang, He, et al.
Published: (2023)
by: Wang, He, et al.
Published: (2023)
Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
by: Zehtabi, Shahryar, et al.
Published: (2022)
by: Zehtabi, Shahryar, et al.
Published: (2022)
Time-varying Mixing Matrix Design for Energy-efficient Decentralized Federated Learning
by: Zhang, Xusheng, et al.
Published: (2025)
by: Zhang, Xusheng, et al.
Published: (2025)
AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix
by: Yue, Yun, et al.
Published: (2023)
by: Yue, Yun, et al.
Published: (2023)
CONGO: Compressive Online Gradient Optimization
by: Carleton, Jeremy, et al.
Published: (2024)
by: Carleton, Jeremy, et al.
Published: (2024)
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization
by: Qin, Zhen, et al.
Published: (2023)
by: Qin, Zhen, et al.
Published: (2023)
Activations and Gradients Compression for Model-Parallel Training
by: Rudakov, Mikhail, et al.
Published: (2024)
by: Rudakov, Mikhail, et al.
Published: (2024)
Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization
by: Li, Jiaxiang, et al.
Published: (2024)
by: Li, Jiaxiang, et al.
Published: (2024)
Accelerating Distributed Optimization: A Primal-Dual Perspective on Local Steps
by: Yang, Junchi, et al.
Published: (2024)
by: Yang, Junchi, et al.
Published: (2024)
Stochastic Controlled Averaging for Federated Learning with Communication Compression
by: Huang, Xinmeng, et al.
Published: (2023)
by: Huang, Xinmeng, et al.
Published: (2023)
Asynchronous Policy Gradient Aggregation for Efficient Distributed Reinforcement Learning
by: Tyurin, Alexander, et al.
Published: (2025)
by: Tyurin, Alexander, et al.
Published: (2025)
GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models
by: Dimlioglu, Tolga, et al.
Published: (2024)
by: Dimlioglu, Tolga, et al.
Published: (2024)
BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated Learning
by: Zhu, Heng, et al.
Published: (2021)
by: Zhu, Heng, et al.
Published: (2021)
Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity
by: Bylinkin, Dmitry, et al.
Published: (2024)
by: Bylinkin, Dmitry, et al.
Published: (2024)
Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
by: Mhanna, Elissa, et al.
Published: (2024)
by: Mhanna, Elissa, et al.
Published: (2024)
LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging
by: Maziane, Yassine, et al.
Published: (2026)
by: Maziane, Yassine, et al.
Published: (2026)
Distributed Saddle-Point Problems: Lower Bounds, Near-Optimal and Robust Algorithms
by: Beznosikov, Aleksandr, et al.
Published: (2020)
by: Beznosikov, Aleksandr, et al.
Published: (2020)
High-Performance Hybrid Algorithm for Minimum Sum-of-Squares Clustering of Infinitely Tall Data
by: Mussabayev, Ravil, et al.
Published: (2023)
by: Mussabayev, Ravil, et al.
Published: (2023)
Distributed Stochastic Momentum Tracking with Local Updates: Achieving Optimal Communication and Iteration Complexities
by: Huang, Kun, et al.
Published: (2025)
by: Huang, Kun, et al.
Published: (2025)
A Communication and Computation Efficient Fully First-order Method for Decentralized Bilevel Optimization
by: Wen, Min, et al.
Published: (2024)
by: Wen, Min, et al.
Published: (2024)
The Privacy Power of Correlated Noise in Decentralized Learning
by: Allouah, Youssef, et al.
Published: (2024)
by: Allouah, Youssef, et al.
Published: (2024)
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation
by: Su, Weijie J., et al.
Published: (2018)
by: Su, Weijie J., et al.
Published: (2018)
Similar Items
-
Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum
by: Zhou, Yuan, et al.
Published: (2025) -
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
by: He, Yutong, et al.
Published: (2023) -
A Stochastic Approximation Approach for Efficient Decentralized Optimization on Random Networks
by: Yau, Chung-Yiu, et al.
Published: (2024) -
A Single-Loop Algorithm for Decentralized Bilevel Optimization
by: Dong, Youran, et al.
Published: (2023) -
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
by: Huang, Kun, et al.
Published: (2023)