Algorithmic Learning in a Random World
Vovk, Vladimir, Gammerman, Alexander, Shafer, Glenn
- 出版商: Springer
- 出版日期: 2023-12-14
- 售價: $7,920
- 貴賓價: 9.5 折 $7,524
- 語言: 英文
- 頁數: 476
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3031066510
- ISBN-13: 9783031066511
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相關分類:
Algorithms-data-structures
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商品描述
作者簡介
Alexander Gammerman is Professor of Computer Science and co-Director of the Centre for Reliable Machine Learning at Royal Holloway, University of London. His research interests lie in machine learning and pattern recognition, where the majority of his research books, papers, and grants can be found. He is a Fellow of the Royal Statistical Society and has held visiting and honorary professorships from several universities in Europe and the USA.
Glenn Shafer is Professor and former Dean of the Rutgers Business School - Newark and New Brunswick. He is best known for his work in the 1970s and 1980s on the Dempster-Shafer theory, an alternative theory of probability that has been applied widely in engineering and artificial intelligence. Glenn is also known for his initiation, with Vladimir Vovk, of the game-theoretic framework for probability. Their first book on the topic was Probability and Finance: It's Only a Game! A new book on the topic, Game-Theoretic Foundations for Probability and Finance, published in 2019 (Wiley).