Cover Image

Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Siqi, Choudhury, Sayantan, Stich, Sebastian U, Loizou, Nicolas
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Extragradient Method for $(L_0, L_1)$-Lipschitz Root-finding Problems
by: Choudhury, Sayantan, et al.
Published: (2025)

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

Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
by: Yoon, TaeHo, et al.
Published: (2025)

Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization
by: Zheng, Tianqi, et al.
Published: (2024)

Efficient Gradient Methods for Distributed Saddle Problems
by: Luo, Ruichen, et al.
Published: (2026)

Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
by: Choudhury, Sayantan, et al.
Published: (2024)

Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
by: Takezawa, Yuki, et al.
Published: (2025)

Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities
by: Emmanouilidis, Konstantinos, et al.
Published: (2024)

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

Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
by: Doikov, Nikita, et al.
Published: (2024)

On Convergence of Incremental Gradient for Non-Convex Smooth Functions
by: Koloskova, Anastasia, et al.
Published: (2023)

Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients
by: Oikonomou, Dimitris, et al.
Published: (2025)

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

Accelerated Distributed Optimization with Compression and Error Feedback
by: Gao, Yuan, et al.
Published: (2025)

Sharpness-Aware Minimization: General Analysis and Improved Rates
by: Oikonomou, Dimitris, et al.
Published: (2025)

Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods
by: Lau, Tim Tsz-Kit, et al.
Published: (2024)

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

Non-convex Stochastic Composite Optimization with Polyak Momentum
by: Gao, Yuan, et al.
Published: (2024)

Non-Convex Federated Optimization under Cost-Aware Client Selection
by: Jiang, Xiaowen, et al.
Published: (2025)

Federated Optimization with Doubly Regularized Drift Correction
by: Jiang, Xiaowen, et al.
Published: (2024)

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters
by: Yukhimchuk, Alexander, et al.
Published: (2026)

Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
by: Luo, Ruichen, et al.
Published: (2025)

Quadratic Gradient: A Unified Framework Bridging Gradient Descent and Newton-Type Methods by Synthesizing Hessians and Gradients
by: Chiang, John
Published: (2022)

Next-Generation Iterative Algorithms for Large-Scale Min-Max Optimization: Design and Analysis
by: Choudhury, Sayantan
Published: (2025)

Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
by: Vankov, Daniil, et al.
Published: (2024)

Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance
by: Oikonomou, Dimitris, et al.
Published: (2024)

Adaptive Sharpness-Aware Minimization with a Polyak-type Step size: A Theory-Grounded Scheduler
by: Oikonomou, Dimitris, et al.
Published: (2026)

Adaptive Delayed-Update Cyclic Algorithm for Variational Inequalities
by: Wei, Yi, et al.
Published: (2026)

Mirror Descent-Type Algorithms for the Variational Inequality Problem with Functional Constraints
by: Alkousa, Mohammad S., et al.
Published: (2026)

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication
by: Patel, Kumar Kshitij, et al.
Published: (2024)

DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
by: Khaled, Ahmed, et al.
Published: (2023)

FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
by: Takezawa, Yuki, et al.
Published: (2025)

On Penalty-based Bilevel Gradient Descent Method
by: Shen, Han, et al.
Published: (2023)

Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
by: Chakrabarti, Kushal, et al.
Published: (2021)

Iterative Pre-Conditioning for Expediting the Gradient-Descent Method: The Distributed Linear Least-Squares Problem
by: Chakrabarti, Kushal, et al.
Published: (2020)

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models
by: Xu, Ziqing, et al.
Published: (2025)

Stochastic Gradient Methods with Preconditioned Updates
by: Sadiev, Abdurakhmon, et al.
Published: (2022)

On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality
by: Xia, Lu, et al.
Published: (2023)

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

Locally Regularized Sparse Graph by Fast Proximal Gradient Descent
by: Sun, Dongfang, et al.
Published: (2024)