Deep Neural Evolution: Deep Learning with Evolutionary Computation
暫譯: 深度神經進化：結合進化計算的深度學習

Iba, Hitoshi, Noman, Nasimul

Deep Neural Evolution: Deep Learning with Evolutionary Computation
  • 出版商: Springer
  • 出版日期: 2020-05-21
  • 售價: $7,920
  • 貴賓價: 9.5 折 $7,524
  • 語言: 英文
  • 頁數: 438
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 9811536848
  • ISBN-13: 9789811536847
  • 相關分類: DeepLearning

    • 海外代購書籍(需單獨結帳)

商品描述

This book delivers the state of the art in deep learning (DL) methods hybridized with evolutionary computation (EC). Over the last decade, DL has dramatically reformed many domains: computer vision, speech recognition, healthcare, and automatic game playing, to mention only a few. All DL models, using different architectures and algorithms, utilize multiple processing layers for extracting a hierarchy of abstractions of data. Their remarkable successes notwithstanding, these powerful models are facing many challenges, and this book presents the collaborative efforts by researchers in EC to solve some of the problems in DL.

EC comprises optimization techniques that are useful when problems are complex or poorly understood, or insufficient information about the problem domain is available. This family of algorithms has proven effective in solving problems with challenging characteristics such as non-convexity, non-linearity, noise, and irregularity, which dampen the performance of most classic optimization schemes. Furthermore, EC has been extensively and successfully applied in artificial neural network (ANN) research --from parameter estimation to structure optimization. Consequently, EC researchers are enthusiastic about applying their arsenal for the design and optimization of deep neural networks (DNN).

This book brings together the recent progress in DL research where the focus is particularly on three sub-domains that integrate EC with DL: (1) EC for hyper-parameter optimization in DNN; (2) EC for DNN architecture design; and (3) Deep neuroevolution. The book also presents interesting applications of DL with EC in real-world problems, e.g., malware classification and object detection. Additionally, it covers recent applications of EC in DL, e.g. generative adversarial networks (GAN) training and adversarial attacks. The book aims to prompt and facilitate the research in DL with EC both in theory and in practice.

商品描述(中文翻譯)

這本書介紹了深度學習（DL）方法與進化計算（EC）相結合的最新技術。在過去十年中，深度學習在許多領域中帶來了顯著的變革：計算機視覺、語音識別、醫療保健以及自動遊戲等，僅舉幾例。所有的深度學習模型，使用不同的架構和算法，利用多層處理來提取數據的抽象層次。儘管這些強大的模型取得了顯著的成功，但它們仍面臨許多挑戰，而本書展示了進化計算領域的研究人員為解決深度學習中的一些問題所做的合作努力。

進化計算包含了在問題複雜或不易理解，或對問題領域的資訊不足時有用的優化技術。這類算法在解決具有挑戰性特徵的問題時已被證明是有效的，例如非凸性、非線性、噪聲和不規則性，這些特徵會削弱大多數經典優化方案的性能。此外，進化計算已在人工神經網絡（ANN）研究中得到廣泛且成功的應用——從參數估計到結構優化。因此，進化計算的研究人員對於將其工具應用於深度神經網絡（DNN）的設計和優化充滿熱情。

本書匯集了深度學習研究中的最新進展，特別關注三個將進化計算與深度學習相結合的子領域：（1）用於DNN的超參數優化的進化計算；（2）DNN架構設計的進化計算；以及（3）深度神經進化。書中還展示了進化計算在現實問題中應用深度學習的有趣案例，例如惡意軟體分類和物體檢測。此外，它還涵蓋了進化計算在深度學習中的最新應用，例如生成對抗網絡（GAN）訓練和對抗攻擊。本書旨在促進和推動深度學習與進化計算在理論和實踐中的研究。

作者簡介

Hitoshi Iba received his Ph.D. degree from The University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory in Ibaraki, Japan. Since 1998, he has been with The University of Tokyo, where he is currently a professor in the Graduate School of Information Science and Technology. His research interests include evolutionary computation, artificial life, artificial intelligence, and robotics. He is an associate editor of the Journal of Genetic Programming and Evolvable Machines (GPEM). Dr. Iba is also is an underwater naturalist and experienced Professional Association of Diving Instructors (PADI) divemaster, having completed more than a thousand dives.

Nasimul Noman received his Ph.D. degree from The University of Tokyo, Japan, in 2007. He was a faculty member in the Department of Computer Science and Engineering, University of Dhaka, Bangladesh, from 2002 to 2012. In 2013, he joined the School of Electrical Engineering and Computing at The University of Newcastle, Australia, and currently he is working as a senior lecturer there. His research interests include evolutionary computation, computational biology, bioinformatics, and machine learning.

作者簡介(中文翻譯)

伊場仁志於1990年獲得日本東京大學的博士學位。從1990年到1998年，他在日本茨城的電氣技術研究所工作。自1998年以來，他一直在東京大學任教，目前是資訊科學與技術研究所的教授。他的研究興趣包括進化計算、人工生命、人工智慧和機器人技術。他是《遺傳編程與可演化機器期刊》（Journal of Genetic Programming and Evolvable Machines, GPEM）的副編輯。伊場博士同時也是一名水下自然學家和經驗豐富的專業潛水教練協會（PADI）潛水長，已完成超過一千次潛水。

納西穆爾·諾曼於2007年獲得日本東京大學的博士學位。他曾於2002年至2012年在孟加拉國達卡大學的計算機科學與工程系任教。2013年，他加入澳大利亞紐卡斯爾大學的電氣工程與計算學院，目前擔任高級講師。他的研究興趣包括進化計算、計算生物學、生物資訊學和機器學習。

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