This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. It begins with the fundamental theory of black-box optimization and proceeds to guide the reader t
Foundations and Trends in Machine Learning | January 2015 , Vol 8(4): pp. 231-357 Publication Download BibTex This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. Starting from the fundamental theory of black-box optimization, the material ...
Convex Optimization Algorithms and Complexity 下载积分: 900 内容提示: Foundations and Trends R?in Machine LearningVol. 8, No. 3-4 (2015) 231–358c ? 2015 S. BubeckDOI: 10.1561/2200000050Convex Optimization: Algorithms andComplexitySébastien BubeckTheory Group, Microsoft Researchsebubeck@microsoft....
Complexity and algorithms for convex network optimization and other nonlinear problems. 4OR, 3(3):171-216, 2005.D.S. Hochbaum, Complexity and algorithms for convex network optimization and other nonlinear problems. Ann. Oper. Res. 153 , 257–296 (2007) MathSciNet MATH...
2017Convex optimization_ Algorithms and complexity阅读笔记 1 介绍一些概念 本专题的总体目标是介绍凸优化中的主要复杂性定理和相应的算法。我们将重点放在凸优化的五个主要结果上,这些结果给出了本文的整体结构:存在具有最优预言复杂度的有效切面方法(第2章),对一阶预言复杂度和曲率之间关系的完整表征。目标函数(第...
2017Convex optimization_ Algorithms and complexity阅读笔记 1 介绍一些概念 本专题的总体目标是介绍凸优化中的主要复杂性定理和相应的算法。我们将重点放在凸优化的五个主要结果上,这些结果给出了本文的整体结构:存在具有最优预言复杂度的有效切面方法(第2章),对一阶预言复杂度和曲率之间关系的完整表征。目标函数(...
Convex Optimization: Algorithms and Complexity 电子书 读后感 评分☆☆☆ 评分☆☆☆ 评分☆☆☆ 评分☆☆☆ 评分☆☆☆ 类似图书 点击查看全场最低价 出版者:Now Publishers Inc 作者:Sébastien Bubeck 出品人: 页数:142 译者: 出版时间:2015 价格:0 ...
the convex optimization methods provide theoretical support for AI model training, which can be viewed as a process of solving an optimization problem. In this chapter, we introduce the foundations of convex optimization algorithms. Particularly, the first- and second-order methods are specified for ...
Particularly, given the inexact initialization oracle, our regularization-based algorithms achieve the best of both worlds - optimal reproducibility and near-optimal gradient complexity - for minimization and minimax optimization. With the inexact gradient oracle, the near-optimal guarantees also hold for ...
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