Explainable, Interpretable, and Transparent AI Systems
暫譯: 可解釋、可詮釋及透明的人工智慧系統

Tripathy, B. K., Seetha, Hari

Explainable, Interpretable, and Transparent AI Systems
  • 出版商: CRC
  • 出版日期: 2026-07-20
  • 售價: $2,820
  • 貴賓價: 9.5 折 $2,679
  • 語言: 英文
  • 頁數: 328
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032580925
  • ISBN-13: 9781032580920
  • 相關分類: Machine Learning

    • 尚未上市，無法訂購

相關主題

商品描述

Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case studies, latest techniques, and applications from domains such as healthcare, finance, and network security. It also covers open-source interpretable tool kits so that practitioners can use them in their domains.

Features:

  • Presents a clear focus on the application of explainable AI systems while tackling important issues of "interpretability" and "transparency".
  • Reviews adept handling with respect to existing software and evaluation issues of interpretability.
  • Provides insights into simple interpretable models such as decision trees, decision rules, and linear regression.
  • Focuses on interpreting black box models like feature importance and accumulated local effects.
  • Discusses capabilities of explainability and interpretability.

This book is aimed at graduate students and professionals in computer engineering and networking communications.

商品描述(中文翻譯)

透明人工智慧（AI）系統促進了對決策過程的理解，並在解釋AI模型的各個方面提供了機會。本書提供了有關可解釋AI領域最新進展的最新資訊，這是AI、機器學習（ML）和深度學習（DL）模型的一項關鍵要求。它提供了來自醫療保健、金融和網絡安全等領域的範例、案例研究、最新技術和應用。它還涵蓋了開源可解釋工具包，以便從業者可以在其領域中使用這些工具。

特色：
- 清楚聚焦於可解釋AI系統的應用，同時處理「可解釋性」和「透明性」的重要議題。
- 評估現有軟體和可解釋性評估問題的熟練處理。
- 提供對簡單可解釋模型的見解，例如決策樹、決策規則和線性回歸。
- 專注於解釋黑箱模型，如特徵重要性和累積局部效應。
- 討論可解釋性和可解釋性的能力。

本書旨在針對計算機工程和網絡通信的研究生和專業人士。

作者簡介

B.K. Tripathy is a distinguished researcher in the fields of Computer Science and Mathematics and is working as a professor (Higher Academic Grade) in the SCORE School of VIT, Vellore. He received his Ph.D. degree in 1983. During his student career, he received three gold medals for securing first position at the graduation level, securing first position at the postgraduate level, and being adjudged as the best postgraduate of the year from Berhampur University, Odisha. He has the distinction of receiving the national scholarship at PG level, UGC (Govt. of India) fellowship for pursuing his research, DST (Govt. of India) fellowship for pursuing M. Tech. (Computer Science) in Pune University, and the SERC fellowship (DOE, Govt. India) for joining IIT Kharagpur as a visiting fellow. He has published more than 740 articles in international journals, proceedings of international conferences of repute, chapters in edited research volumes. Also, he has edited 11 research volumes, written two books and two monographs. He has acted as member of international advisory committee/Technical Program Committee of more than 140 international conferences and in some of them has delivered the key note addresses.

Hari Seetha obtained her master's degree from the National Institute of Technology (formerly R.E.C.) Warangal and obtained her Ph.D. from the School of Computer Science and Engineering, VIT University, Vellore, India. She worked on Large Data Classification during her Ph.D. She has research interests in the fields of pattern recognition, data mining, text mining, soft computing, XAI, IDS, and machine learning. She received the Best Paper Award for the paper entitled "On improving the generalization of SVM Classifier" at the Fifth International Conference on Information Processing held at Bangalore. She has published several research papers in national and international journals of repute. She has been one of the editors for the edited volume, Modern Technologies for Big Data Classification and Clustering published in 2017. She is a member of editorial board for various international journals.

作者簡介(中文翻譯)

B.K. Tripathy 是計算機科學和數學領域的傑出研究者，目前擔任維洛爾 VIT 的 SCORE 學校的教授（高級學術職級）。他於1983年獲得博士學位。在學生生涯中，他因在畢業階段獲得第一名、在研究生階段獲得第一名以及被評為奧迪沙邦 Berhampur 大學的最佳研究生而獲得三枚金牌。他在研究生階段獲得國家獎學金，並獲得印度政府的 UGC 獎學金以進行研究，還獲得印度政府的 DST 獎學金以在普納大學攻讀計算機科學碩士學位，以及印度政府 DOE 的 SERC 獎學金以作為訪問學者加入 IIT Kharagpur。他在國際期刊、知名國際會議的會議論文集以及編輯的研究卷中發表了超過740篇文章。此外，他編輯了11本研究卷，撰寫了兩本書和兩本專著。他曾擔任140多個國際會議的國際諮詢委員會/技術程序委員會成員，並在其中一些會議上發表了主題演講。

Hari Seetha 於國立技術學院（前身為 R.E.C.）獲得碩士學位，並在印度維洛爾的 VIT 大學計算機科學與工程學院獲得博士學位。她在博士期間研究大型數據分類。她的研究興趣包括模式識別、數據挖掘、文本挖掘、軟計算、可解釋人工智慧（XAI）、入侵檢測系統（IDS）和機器學習。她因在第五屆國際信息處理會議上發表的論文《改善 SVM 分類器的泛化能力》而獲得最佳論文獎。她在國內外知名期刊上發表了多篇研究論文。她曾擔任2017年出版的編輯卷《大數據分類與聚類的現代技術》的編輯之一。她是多本國際期刊的編輯委員會成員。

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