We first delve into first-order optimization methods in convex optimization, offering a unified convergence analysis through the lens of strong Lyapunov conditions. Prevailing first-order optimization algorithms such as proximal gradient methods, heavy ball methods (also known as momentum methods), ...
1、stochastic gradient descent随机梯度下降 2、gradient descent梯度下降 而stochastic随机 形容词 random随机, 任意, 乱, 随便, 轻淡, 胡乱的 stochastic随机 1）Stochastic and mathematical models;随机和数学模型；2）In this paper, a numerical method for structure stochastic response analysis is pr...
Semi-Stochastic Gradient Descent Methods In this paper we study the problem of minimizing the average of a large number ($n$) of smooth convex loss functions. We propose a new method, S2GD (Semi-S... K Jakub,R Peter - 《Mathematics》 被引量: 83发表: 2017年 Error Analysis of Stochasti...
282(机器学习理论篇6)33 Fisher Discriminant Analysis - 1 13:53 283(机器学习理论篇6)33 Fisher Discriminant Analysis - 2 13:55 284(机器学习理论篇6)33 Fisher Discriminant Analysis - 3 13:57 285(机器学习理论篇6)34 Kernel FDA - 1 14:12 286(机器学习理论篇6)34 Kernel FDA - 2 14:14 287...
Stochastic gradient descent (SGD) has been widely used in machine learning due to its computational efficiency and favorable generalization properties. Recently, it has been empirically demonstrated that the gradient noise in several deep learning settings admits a non-Gaussian, heavy-tailed behavior. ...
内容提示: Stochastic Gradient Descent Jittering for Inverse Problems:Alleviating the Accuracy-Robustness TradeoffPeimeng Guan1 , Mark A. Davenport 1Georgia Intitute of TechnologyAtlanta, GA 30332 USA{pguan6, mdav}@gatech.eduAbstractInverse problems aim to reconstruct unseen data from cor-rupted or ...
Stochastic gradient descent on Riemannian manifolds:黎曼流形上的随机梯度下降on,梯度,梯度下降,黎曼流形上,下降 文档格式: .pdf 文档大小: 387.51K 文档页数: 29页 顶/踩数: 0/0 收藏人数: 2 评论次数: 0 文档热度: 文档分类: 论文--毕业论文
Learning characteristics of stochastic-gradient-descent algorithms: A general study, analysis, and critique 喜欢 0 阅读量: 371 作者: WA Gardner 摘要: A comprehensive analysis of the mean-square learning characteristics of stochastic-descent algorithms is presented. The approach is based on the ...
Stochastic Gradient Descent for Two-layer Neural Networks 下载积分: 199 内容提示: arXiv:2407.07670v1 [stat.ML] 10 Jul 2024Stochastic Gradient Descent for Two-layer Neural Networks †Dinghao Cao 1 , Zheng-Chu Guo 1 and Lei Shi 21School of Mathematical Sciences, Zhejiang University, Hangzhou ...
We consider stochastic gradient descent and its averaging variant for binary classification problems in a reproducing kernel Hilbert space. In the traditional analysis using a consistency property of loss functions, it is known that the expected classification error converges more slowly than the expected...