Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
Fuente:
arXiv
Saved in:
| Main Authors: | He, Yutong, Huang, Xinmeng, Chen, Yiming, Yin, Wotao, Yuan, Kun |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
by: He, Yutong, et al.
Published: (2023)
by: He, Yutong, et al.
Published: (2023)
Stochastic Controlled Averaging for Federated Learning with Communication Compression
by: Huang, Xinmeng, et al.
Published: (2023)
by: Huang, Xinmeng, 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)
An Accelerated Distributed Stochastic Gradient Method with Momentum
by: Huang, Kun, et al.
Published: (2024)
by: Huang, Kun, et al.
Published: (2024)
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)
A GPU-Accelerated Distributed Algorithm for Optimal Power Flow in Distribution Systems
by: Ryu, Minseok, et al.
Published: (2025)
by: Ryu, Minseok, et al.
Published: (2025)
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)
An Optimistic Gradient Tracking Method for Distributed Minimax Optimization
by: Huang, Yan, et al.
Published: (2025)
by: Huang, Yan, et al.
Published: (2025)
Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction
by: Tyurin, Alexander
Published: (2025)
by: Tyurin, Alexander
Published: (2025)
Optimizing Stochastic Gradient Push under Broadcast Communications
by: Nguyen, Tuan, et al.
Published: (2026)
by: Nguyen, Tuan, et al.
Published: (2026)
Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization
by: Li, Jiaxiang, et al.
Published: (2024)
by: Li, Jiaxiang, et al.
Published: (2024)
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems
by: Li, Junyi, et al.
Published: (2023)
by: Li, Junyi, et al.
Published: (2023)
A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration
by: Hu, Yuchen, et al.
Published: (2025)
by: Hu, Yuchen, et al.
Published: (2025)
From Sequential to Parallel: Reformulating Dynamic Programming as GPU Kernels for Large-Scale Stochastic Combinatorial Optimization
by: Zhao, Jingyi, et al.
Published: (2026)
by: Zhao, Jingyi, et al.
Published: (2026)
Momentum-based Accelerated Algorithm for Distributed Optimization under Sector-Bound Nonlinearity
by: Doostmohammadian, Mohammadreza, et al.
Published: (2025)
by: Doostmohammadian, Mohammadreza, et al.
Published: (2025)
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)
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
by: Huang, Kun, et al.
Published: (2023)
by: Huang, Kun, et al.
Published: (2023)
Decentralized Distributed Optimization for Saddle Point Problems
by: Rogozin, Alexander, et al.
Published: (2021)
by: Rogozin, Alexander, et al.
Published: (2021)
Tailoring Gradient Methods for Differentially-Private Distributed Optimization
by: Wang, Yongqiang, et al.
Published: (2022)
by: Wang, Yongqiang, et al.
Published: (2022)
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)
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks
by: Heydaribeni, Nasimeh, et al.
Published: (2023)
by: Heydaribeni, Nasimeh, et al.
Published: (2023)
Distributed Constraint-Coupled Optimization: Harnessing ADMM-consensus for robustness
by: Messilem, Mohamed Abdelmouamin, et al.
Published: (2025)
by: Messilem, Mohamed Abdelmouamin, et al.
Published: (2025)
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)
One-Point Feedback for Composite Optimization with Applications to Distributed and Federated Learning
by: Beznosikov, Aleksandr, et al.
Published: (2021)
by: Beznosikov, Aleksandr, et al.
Published: (2021)
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression
by: Condat, Laurent, et al.
Published: (2024)
by: Condat, Laurent, 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)
Improving the Bit Complexity of Communication for Distributed Convex Optimization
by: Ghadiri, Mehrdad, et al.
Published: (2024)
by: Ghadiri, Mehrdad, et al.
Published: (2024)
D-PDLP: Scaling PDLP to Distributed Multi-GPU Systems
by: Li, Hongpei, et al.
Published: (2026)
by: Li, Hongpei, et al.
Published: (2026)
A Single-Loop Algorithm for Decentralized Bilevel Optimization
by: Dong, Youran, et al.
Published: (2023)
by: Dong, Youran, et al.
Published: (2023)
On Biased Compression for Distributed Learning
by: Beznosikov, Aleksandr, et al.
Published: (2020)
by: Beznosikov, Aleksandr, et al.
Published: (2020)
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes
by: Huang, Yan, et al.
Published: (2024)
by: Huang, Yan, et al.
Published: (2024)
GPU-Accelerated Primal Heuristics for Mixed Integer Programming
by: Çördük, Akif, et al.
Published: (2025)
by: Çördük, Akif, et al.
Published: (2025)
Decentralized Nonsmooth Nonconvex Optimization with Client Sampling
by: Chen, Xinyan, et al.
Published: (2026)
by: Chen, Xinyan, et al.
Published: (2026)
Communication-Efficient Federated Optimization over Semi-Decentralized Networks
by: Wang, He, et al.
Published: (2023)
by: Wang, He, et al.
Published: (2023)
CONGO: Compressive Online Gradient Optimization
by: Carleton, Jeremy, et al.
Published: (2024)
by: Carleton, Jeremy, 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)
A First-Order Algorithm for Decentralised Min-Max Problems
by: Malitsky, Yura, et al.
Published: (2023)
by: Malitsky, Yura, et al.
Published: (2023)
dHPR: A Distributed Halpern Peaceman--Rachford Method for Non-smooth Distributed Optimization Problems
by: Feng, Zhangcheng, et al.
Published: (2025)
by: Feng, Zhangcheng, et al.
Published: (2025)
Accelerating Optimal Power Flow with GPUs: SIMD Abstraction of Nonlinear Programs and Condensed-Space Interior-Point Methods
by: Shin, Sungho, et al.
Published: (2023)
by: Shin, Sungho, et al.
Published: (2023)
Load Balancing with Network Latencies via Distributed Gradient Descent
by: Balseiro, Santiago R., et al.
Published: (2025)
by: Balseiro, Santiago R., et al.
Published: (2025)
Similar Items
-
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
by: He, Yutong, et al.
Published: (2023) -
Stochastic Controlled Averaging for Federated Learning with Communication Compression
by: Huang, Xinmeng, et al.
Published: (2023) -
Distributed Stochastic Momentum Tracking with Local Updates: Achieving Optimal Communication and Iteration Complexities
by: Huang, Kun, et al.
Published: (2025) -
An Accelerated Distributed Stochastic Gradient Method with Momentum
by: Huang, Kun, et al.
Published: (2024) -
Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity
by: Bylinkin, Dmitry, et al.
Published: (2024)