自适应梯度优化算法简介

Mouna Lamine, Sang-Chul Kim
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引用次数: 0

摘要

机器学习由于几乎无限的可用数据量而面临着快速的发展,并且在各个领域得到了广泛的应用。优化是机器学习的核心组成部分之一,越来越受到研究者的关注。近年来,人们在改进机器学习中的优化方法方面做了大量的工作。本文将介绍自适应梯度算法(Adapg),这是自适应学习族优化算法的一个新的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Introduction of Optimization Algorithm for Adaptive Gradient
Machine Learning is facing rapid development due to the almost unlimited amount of data available, and it is widely applied in diverse areas. Optimization is one of the core components in the machine learning which attracted more researcher's attention to it. In recent years there has been a great deal of work on improving optimisation methods in machine learning. In this paper we will introduce the Adaptive Gradient(Adapg), a new extension in the adaptive learning family Optimization algorithm.
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