Imagen de Portada

Beyond Scaffold: A Unified Spatio-Temporal Gradient Tracking Method

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Huang, Yan, Xu, Jinming, Chen, Jiming, Johansson, Karl Henrik
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Optimization and Control 90C06
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Fully First-Order Methods for Decentralized Bilevel Optimization
por: Wang, Xiaoyu, et al.
Publicado: (2024)

Variance-Reduced Fast Operator Splitting Methods for Generalized Equations
por: Tran-Dinh, Quoc
Publicado: (2025)

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

Revisiting Extragradient-Type Methods -- Part 1: Generalizations and Sublinear Convergence Rates
por: Tran-Dinh, Quoc, et al.
Publicado: (2024)

Variance-Reduced Fast Krasnoselkii-Mann Methods for Finite-Sum Root-Finding Problems
por: Tran-Dinh, Quoc
Publicado: (2024)

NewVEM: A Newton Vertex Exchange Method for a Class of Constrained Self-Concordant Minimization Problems
por: Liang, Ling, et al.
Publicado: (2024)

Accelerated Extragradient-Type Methods -- Part 2: Generalization and Sublinear Convergence Rates under Co-Hypomonotonicity
por: Tran-Dinh, Quoc, et al.
Publicado: (2025)

Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
por: Lin, Zhenwei, et al.
Publicado: (2022)

Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients
por: Garg, Sachin, et al.
Publicado: (2024)

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

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

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

An Optimistic Gradient Tracking Method for Distributed Minimax Optimization
por: Huang, Yan, et al.
Publicado: (2025)

Fast Computation of Superquantile-Constrained Optimization Through Implicit Scenario Reduction
por: Roth, Jake, et al.
Publicado: (2024)

Randomized Subspace Nesterov Accelerated Gradient
por: Omiya, Gaku, et al.
Publicado: (2026)

Faster Adaptive Optimization via Expected Gradient Outer Product Reparameterization
por: DePavia, Adela, et al.
Publicado: (2025)

Beyond Suspension: A Two-phase Methodology for Concluding Sports Leagues
por: Hassanzadeh, Ali, et al.
Publicado: (2024)

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

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

A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction
por: Milzarek, Andre, et al.
Publicado: (2022)

Peaceman-Rachford Splitting Method Converges Ergodically for Solving Convex Optimization Problems
por: Chen, Kaihuang, et al.
Publicado: (2025)

A Projection-Free Method for Solving Convex Bilevel Optimization Problems
por: Giang-Tran, Khanh-Hung, et al.
Publicado: (2023)

Stochastic versus Deterministic in Stochastic Gradient Descent
por: Li, Runze, et al.
Publicado: (2025)

A Sparse Smoothing Newton Method for Solving Discrete Optimal Transport Problems
por: Hou, Di, et al.
Publicado: (2023)

Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth
por: Davis, Damek, et al.
Publicado: (2024)

Stochastic Variance-Reduced Forward-Reflected-Backward Splitting Methods for Nonmonotone Generalized Equations
por: Tran-Dinh, Quoc
Publicado: (2024)

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

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

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

Stability and convergence analysis of AdaGrad for non-convex optimization via novel stopping time-based techniques
por: Jin, Ruinan, et al.
Publicado: (2024)

A Corrected Inexact Proximal Augmented Lagrangian Method with a Relative Error Criterion for a Class of Group-quadratic Regularized Optimal Transport Problems
por: Yang, Lei, et al.
Publicado: (2023)

Representation and Regression Problems in Neural Networks: Relaxation, Generalization, and Numerics
por: Liu, Kang, et al.
Publicado: (2024)

A New Kernel Regularity Condition for Distributed Mirror Descent: Broader Coverage and Simpler Analysis
por: Qiu, Junwen, et al.
Publicado: (2026)

On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms
por: Latafat, Puya, et al.
Publicado: (2023)

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

Adaptive proximal gradient methods are universal without approximation
por: Oikonomidis, Konstantinos A., et al.
Publicado: (2024)

Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient
por: Latafat, Puya, et al.
Publicado: (2023)

Safeguarding adaptive methods: global convergence of Barzilai-Borwein and other stepsize choices
por: Ou, Hongjia, et al.
Publicado: (2024)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
por: Bao, Chenglong, et al.
Publicado: (2024)