國立虎尾科技大學 |

Mathematical analysis of machine learning algorithms

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Mathematical analysis of machine learning algorithms/ Tong Zhang, Hong Kong University of Science and Technology.
作者:	Zhang, Tong,
出版者:	Cambridge, United Kingdom ;Cambridge University Press, : 2023.,
面頁冊數:	xiii, 453 p. :ill., digital ; : 26 cm.;
附註:	Title from publisher's bibliographic system (viewed on 31 Jul 2023).
標題:	Artificial intelligence - Congresses. - Mathematics -
電子資源:	https://doi.org/10.1017/9781009093057
ISBN:	9781009093057

Mathematical analysis of machine learning algorithms
Zhang, Tong,1971-

Mathematical analysis of machine learning algorithms[electronic resource] /Tong Zhang, Hong Kong University of Science and Technology. - Cambridge, United Kingdom ;Cambridge University Press,2023. - xiii, 453 p. :ill., digital ;26 cm.

Title from publisher's bibliographic system (viewed on 31 Jul 2023).

The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and researchers of AI to the main mathematical techniques used to analyze machine learning algorithms, with motivations and applications. Topics covered include the analysis of supervised learning algorithms in the iid setting, the analysis of neural networks (e.g. neural tangent kernel and mean-field analysis), and the analysis of machine learning algorithms in the sequential decision setting (e.g. online learning, bandit problems, and reinforcement learning). Students will learn the basic mathematical tools used in the theoretical analysis of these machine learning problems and how to apply them to the analysis of various concrete algorithms. This textbook is perfect for readers who have some background knowledge of basic machine learning methods, but want to gain sufficient technical knowledge to understand research papers in theoretical machine learning.

ISBN: 9781009093057Subjects--Topical Terms:

884619
Artificial intelligence
--Mathematics--Congresses.

LC Class. No.: Q325.5 / .Z43 2023

Dewey Class. No.: 006.31

Mathematical analysis of machine learning algorithms
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500 $a Title from publisher's bibliographic system (viewed on 31 Jul 2023).
520 $a The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and researchers of AI to the main mathematical techniques used to analyze machine learning algorithms, with motivations and applications. Topics covered include the analysis of supervised learning algorithms in the iid setting, the analysis of neural networks (e.g. neural tangent kernel and mean-field analysis), and the analysis of machine learning algorithms in the sequential decision setting (e.g. online learning, bandit problems, and reinforcement learning). Students will learn the basic mathematical tools used in the theoretical analysis of these machine learning problems and how to apply them to the analysis of various concrete algorithms. This textbook is perfect for readers who have some background knowledge of basic machine learning methods, but want to gain sufficient technical knowledge to understand research papers in theoretical machine learning.
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650 0 $a Machine learning $x Mathematics $v Textbooks. $3 1446621
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