带局部步骤的分散梯度跟踪

IF 1.4 3区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Yue Liu, Tao Lin, Anastasia Koloskova, Sebastian U. Stich
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引用次数: 0

摘要

梯度跟踪(GT)是一种用于解决网络分散优化问题(如训练机器学习模型)的算法。梯度跟踪算法的一个关键特征是跟踪机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decentralized gradient tracking with local steps
Gradient tracking (GT) is an algorithm designed for solving decentralized optimization problems over a network (such as training a machine learning model). A key feature of GT is a tracking mechani...
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来源期刊
Optimization Methods & Software
Optimization Methods & Software 工程技术-计算机:软件工程
CiteScore
4.50
自引率
0.00%
发文量
40
审稿时长
7 months
期刊介绍: Optimization Methods and Software publishes refereed papers on the latest developments in the theory and realization of optimization methods, with particular emphasis on the interface between software development and algorithm design. Topics include: Theory, implementation and performance evaluation of algorithms and computer codes for linear, nonlinear, discrete, stochastic optimization and optimal control. This includes in particular conic, semi-definite, mixed integer, network, non-smooth, multi-objective and global optimization by deterministic or nondeterministic algorithms. Algorithms and software for complementarity, variational inequalities and equilibrium problems, and also for solving inverse problems, systems of nonlinear equations and the numerical study of parameter dependent operators. Various aspects of efficient and user-friendly implementations: e.g. automatic differentiation, massively parallel optimization, distributed computing, on-line algorithms, error sensitivity and validity analysis, problem scaling, stopping criteria and symbolic numeric interfaces. Theoretical studies with clear potential for applications and successful applications of specially adapted optimization methods and software to fields like engineering, machine learning, data mining, economics, finance, biology, or medicine. These submissions should not consist solely of the straightforward use of standard optimization techniques.
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