Large-Scale Convex Optimization: Algorithms & Analyses Via Monotone Operators
暫譯: 大規模凸優化:透過單調運算元的演算法與分析

Ryu, Ernest K., Yin, Wotao

  • 出版商: Cambridge
  • 出版日期: 2022-12-01
  • 售價: $3,010
  • 貴賓價: 9.5$2,860
  • 語言: 英文
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1009160850
  • ISBN-13: 9781009160858
  • 相關分類: Algorithms-data-structures
  • 海外代購書籍(需單獨結帳)

商品描述

Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods - including parallel-distributed algorithms - through the abstraction of monotone operators. With the increased computational power and availability of big data over the past decade, applied disciplines have demanded that larger and larger optimization problems be solved. This text covers the first-order convex optimization methods that are uniquely effective at solving these large-scale optimization problems. Readers will have the opportunity to construct and analyze many well-known classical and modern algorithms using monotone operators, and walk away with a solid understanding of the diverse optimization algorithms. Graduate students and researchers in mathematical optimization, operations research, electrical engineering, statistics, and computer science will appreciate this concise introduction to the theory of convex optimization algorithms.

商品描述(中文翻譯)

本書從第一門凸優化課程的結尾開始,統一分析一階優化方法,包括平行分佈算法,透過單調算子的抽象化來進行。隨著過去十年計算能力的提升和大數據的可用性,應用領域要求解決越來越大的優化問題。本書涵蓋了一階凸優化方法,這些方法在解決這些大規模優化問題時具有獨特的有效性。讀者將有機會使用單調算子構建和分析許多著名的經典和現代算法,並對各種優化算法有深入的理解。數學優化、運籌學、電機工程、統計學和計算機科學的研究生和研究人員將會欣賞這本對凸優化算法理論的簡明介紹。