Cover Image

A New Kernel Regularity Condition for Distributed Mirror Descent: Broader Coverage and Simpler Analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Qiu, Junwen, Zeng, Ziyang, Mei, Leilei, Zhang, Junyu
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control Distributed, Parallel, and Cluster Computing Machine Learning 90C06, 90C30, 90C26
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Shuffling the Stochastic Mirror Descent via Dual Lipschitz Continuity and Kernel Conditioning
by: Qiu, Junwen, et al.
Published: (2026)

Pareto-optimal Trade-offs Between Communication and Computation with Flexible Gradient Tracking
by: Huang, Yan, et al.
Published: (2025)

Accelerating Deterministic Global Optimization via GPU-parallel Interval Arithmetic
by: Zhang, Hongzhen, et al.
Published: (2025)

A KL-based Analysis Framework with Applications to Non-Descent Optimization Methods
by: Qiu, Junwen, et al.
Published: (2024)

Large-Scale Linear Energy System Optimization: A Systematic Review on Parallelization Strategies via Decomposition
by: Hadidi, Lars, et al.
Published: (2025)

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
by: Higuchi, Rei, et al.
Published: (2024)

A new envelope function for nonsmooth DC optimization
by: Themelis, Andreas, et al.
Published: (2020)

On convergence of a $q$-random coordinate constrained algorithm for non-convex problems
by: Ghaffari-Hadigheh, Alireza, et al.
Published: (2022)

nvPAX: Constrained Optimization for Dynamic Power Allocation in Hierarchical and Multi-Tenant Systems
by: Sivan, Hadar, et al.
Published: (2026)

New vector transport operators extending a Riemannian CG algorithm to generalized Stiefel manifold with low-rank applications
by: Wang, Xuejie, et al.
Published: (2023)

On Tackling High-Dimensional Nonconvex Stochastic Optimization via Stochastic First-Order Methods with Non-smooth Proximal Terms and Variance Reduction
by: Xie, Yue, et al.
Published: (2025)

Decentralized projected Riemannian stochastic recursive momentum method for nonconvex optimization
by: Deng, Kangkang, et al.
Published: (2024)

Random Reshuffling with Momentum for Nonconvex Problems: Iteration Complexity and Last Iterate Convergence
by: Qiu, Junwen, et al.
Published: (2024)

High Probability Guarantees for Random Reshuffling
by: Yu, Hengxu, et al.
Published: (2023)

Alternating minimization for square root principal component pursuit
by: Deng, Shengxiang, et al.
Published: (2024)

Stochastic First-Order Methods with Non-smooth and Non-Euclidean Proximal Terms for Nonconvex High-Dimensional Stochastic Optimization
by: Xie, Yue, et al.
Published: (2024)

Global Solutions to Non-Convex Functional Constrained Problems with Hidden Convexity
by: Fatkhullin, Ilyas, et al.
Published: (2025)

Stochastic Optimization under Hidden Convexity
by: Fatkhullin, Ilyas, et al.
Published: (2023)

A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization
by: Qiu, Junwen, et al.
Published: (2023)

Effective Front-Descent Algorithms with Convergence Guarantees
by: Lapucci, Matteo, et al.
Published: (2024)

Efficient parallel implementation of the multiplicative weight update method for graph-based linear programs
by: Ju, Caleb, et al.
Published: (2023)

Level Constrained First Order Methods for Function Constrained Optimization
by: Boob, Digvijay, et al.
Published: (2022)

Fast Frank--Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions
by: Takahashi, Shota, et al.
Published: (2025)

PANOC-lite: A simpler and more efficient algorithm for composite minimization
by: Bodard, Alexander, et al.
Published: (2026)

Stochastic Algorithms for Large-Scale Composite Optimization: the Case of Single-Shot X-FEL Imaging
by: Luke, D. Russell, et al.
Published: (2024)

Proximal Limited-Memory Quasi-Newton Methods for Nonsmooth Nonconvex Optimization
by: Dahl, Simeon vom, et al.
Published: (2026)

Randomized block proximal method with locally Lipschitz continuous gradient
by: Pérez-Aros, Pedro, et al.
Published: (2025)

Bilevel Learning via Inexact Stochastic Gradient Descent
by: Salehi, Mohammad Sadegh, et al.
Published: (2025)

pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization
by: Sen, Mrinmay, et al.
Published: (2025)

A Generalized Version of Chung's Lemma and its Applications
by: Jiang, Li, et al.
Published: (2024)

A Normal Map-Based Proximal Stochastic Gradient Method: Convergence and Identification Properties
by: Qiu, Junwen, et al.
Published: (2023)

A Stochastic Gradient Descent Method for Globally Minimizing Nearly Convex Functions
by: Bao, Chenglong, et al.
Published: (2025)

Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence
by: Fatkhullin, Ilyas, et al.
Published: (2024)

Some optimality conditions of set-valued optimization problems in locally convex topological vector spaces
by: Zeng, Renying
Published: (2024)

Accelerated Training of Federated Learning via Second-Order Methods
by: Sen, Mrinmay, et al.
Published: (2025)

Optimality Conditions and Duality for Multiobjective Fractional Bilevel Optimization Problems
by: Lara, Felipe, et al.
Published: (2025)

Cardinality-Constrained Multi-Objective Optimization: Novel Optimality Conditions and Algorithms
by: Lapucci, Matteo, et al.
Published: (2023)

On a globally convergent semismooth* Newton method in nonsmooth nonconvex optimization
by: Gfrerer, H.
Published: (2024)

Globally Solving Concave Quadratic Programs via Doubly Nonnegative Relaxation
by: Qu, Zheng, et al.
Published: (2023)

Tractable downfall of basis pursuit in structured sparse optimization
by: Marmary, Maya V., et al.
Published: (2025)