尼希斯·K·维什诺伊：凸优化算法 Algorithms for Convex Optimization

基本信息

Format:Paperback / softback 200 pages, Worked examples or Exercises

Publisher:Cambridge University Press

Imprint:Cambridge University Press

ISBN:9781108741774

Published:7 Oct 2021

Weight:510g

Dimensions:152 x 228 x 23 (mm)

页面参数仅供参考，具体以实物为准

书籍简介

在过去的几年中，凸优化算法彻底改变了离散和连续优化问题的算法设计。对于大流、大匹配和子模函数小化等问题，很快的算法涉及梯度下降、镜像下降、内点法和椭圆体法等基本方法。这本独立的书的目标是使计算机科学、数据科学和机器学习领域的研究人员和专业人士能够深入了解这些算法。文本强调了如何从初原理推导出凸优化的关键算法以及如何建立准确的运行时间界限。这篇现代文本解释了这些算法在离散优化问题中的成功，以及这些方法如何显著推动了凸优化本身的新发展。

In the last few years, Algorithms for Convex Optimization have revolutionized algorithm design, both for discrete and continuous optimization problems. For problems like maximum flow, maximum matching, and submodular function minimization, the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods. The goal of this self-contained book is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds. This modern text explains the success of these algorithms in problems of discrete optimization, as well as how these methods have significantly pushed the state of the art of convex optimization itself.

作者简介

Nisheeth K. Vishnoi 是耶鲁大学计算机科学教授。他的研究领域包括理论计算机科学、优化和机器学习。他曾获得 2005 年 IEEE FOCS论文奖、2006 年 IBM 研究 Pat Goldberg 纪念奖、2011 年印度国家科学院青年科学家奖和 2019 年 ACM FAccT论文奖。他于 2019 年当选为 ACM 会士。他获得了孟买印度理工学院计算机科学与工程学士学位和佐治亚理工学院算法、组合学和优化博士学位。

Nisheeth K. Vishnoi is a Professor of Computer Science at Yale University. His research areas include theoretical computer science, optimization, and machine learning. He is a recipient of the Best Paper Award at IEEE FOCS in 2005, the IBM Research Pat Goldberg Memorial Award in 2006, the Indian National Science Academy Young Scientist Award in 2011, and the Best Paper award at ACM FAccT in 2019. He was elected an ACM Fellow in 2019. He obtained a bachelor degree in Computer Science and Engineering from IIT Bombay and a Ph.D. in Algorithms, Combinatorics and Optimization from Georgia Institute of Technology.