Stochastic Optimization for Large-Scale Machine Learning
暫譯: 大規模機器學習的隨機優化

Chauhan, Vinod Kumar

Stochastic Optimization for Large-Scale Machine Learning
  • 出版商: CRC
  • 出版日期: 2021-11-19
  • 售價: $6,820
  • 貴賓價: 9.5 折 $6,479
  • 語言: 英文
  • 頁數: 158
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032131756
  • ISBN-13: 9781032131757
  • 相關分類: Machine Learning

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Advancements in the technology and availability of data sources have led to the Big Data' era. Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of challenges such as slow training and scalability of machine learning models. One of the major challenges in machine learning is to develop efficient and scalable learning algorithms, i.e., optimization techniques to solve large scale learning problems.

Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods.

Key Features:

  • Bridges machine learning and Optimisation.
  • Bridges theory and practice in machine learning.
  • Identifies key research areas and recent research directions to solve large-scale machine learning problems.
  • Develops optimisation techniques to improve machine learning algorithms for big data problems.

The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning.

商品描述(中文翻譯)

科技的進步和數據來源的可用性促成了「大數據」時代的到來。處理大量數據提供了揭示更細緻模式的潛力，並能夠做出及時且準確的決策，但同時也帶來了許多挑戰，例如機器學習模型的訓練速度慢和可擴展性問題。機器學習中的一個主要挑戰是開發高效且可擴展的學習算法，即解決大規模學習問題的優化技術。

大規模機器學習的隨機優化識別了不同的改進領域和近期的研究方向，以應對這一挑戰。開發的優化技術也被探討，以改善基於數據訪問的機器學習算法，以及一階和二階優化方法。

主要特點：

  • 橋接機器學習與優化。
  • 橋接機器學習中的理論與實踐。
  • 識別解決大規模機器學習問題的關鍵研究領域和近期研究方向。
  • 開發優化技術以改善大數據問題的機器學習算法。

本書將成為機器學習領域的從業者、研究者以及學生的重要參考資料。

作者簡介

Dr. Vinod Kumar Chauhan is a Research Associate in Industrial Machine Learning in the Institute for Manufacturing, Department of Engineering at University of Cambridge UK. He has a PhD in Machine Learning from Panjab University Chandigarh India. His research interests are in Machine Learning, Optimization and Network Science. He specializes in solving large-scale optimization problems in Machine Learning, handwriting recognition, flight delay propagation in airlines, robustness and nestedness in complex networks and supply chain design using mathematical programming, genetic algorithms and reinforcement learning.

作者簡介(中文翻譯)

Dr. Vinod Kumar Chauhan 是英國劍橋大學工程系製造研究所的工業機器學習研究助理。他擁有印度昌迪加爾的旁遮普大學機器學習博士學位。他的研究興趣包括機器學習、優化和網絡科學。他專注於解決機器學習中的大規模優化問題、手寫識別、航空公司航班延誤傳播、複雜網絡中的穩健性和嵌套性，以及使用數學規劃、遺傳算法和強化學習進行供應鏈設計。

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