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Sep, 2017
GIANT: 分布式优化的全局改进近似牛顿方法
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization
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Shusen Wang, Farbod Roosta-Khorasani, Peng Xu, Michael W. Mahoney
TL;DR
本研究提出了一种分布式和通信高效的牛顿类型优化方法,名为GIANT,通过利用全球ANT方向进行局部计算和全局通信之间的折衷来改善收敛率,并仅涉及一个调整参数。
Abstract
For
distributed computing
environments, we consider the canonical machine learning problem of
empirical risk minimization
(ERM) with quadratic regularization, and we propose a distributed and
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