東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Mathematical analysis of machine learning algorithms

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mathematical analysis of machine learning algorithms/ Tong Zhang, Hong Kong University of Science and Technology.
Author:	Zhang, Tong,
Published:	Cambridge, United Kingdom ;Cambridge University Press, : 2023.,
Description:	xiii, 453 p. :ill., digital ;26 cm.
Notes:	Title from publisher's bibliographic system (viewed on 31 Jul 2023).
Subject:	Machine learning - Textbooks. - Mathematics -
Online resource:	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:

3526635
Machine learning
--Mathematics--Textbooks.

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

Dewey Class. No.: 006.31

Mathematical analysis of machine learning algorithms
LDR:01960nmm a2200253 a 4500 001 2378185
003 UkCbUP
005 20230731021710.0
006 m d
007 cr nn 008maaau
008 250304s2023 enk o 1 0 eng d
020 $a 9781009093057 $q (electronic bk.)
020 $a 9781009098380 $q (hardback)
035 $a CR9781009093057
040 $a UkCbUP $b eng $c UkCbUP $d GP
041 0 $a eng
050 0 0 $a Q325.5 $b .Z43 2023
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .Z63 2023
100 1 $a Zhang, Tong, $d 1971- $3 3729339
245 1 0 $a Mathematical analysis of machine learning algorithms $h [electronic resource] / $c Tong Zhang, Hong Kong University of Science and Technology.
260 $a Cambridge, United Kingdom ; $a New York, NY : $b Cambridge University Press, $c 2023.
300 $a xiii, 453 p. : $b ill., digital ; $c 26 cm.
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.
650 0 $a Machine learning $x Mathematics $v Textbooks. $3 3526635
650 0 $a Artificial intelligence $x Mathematics $v Textbooks. $3 3526636
856 4 0 $u https://doi.org/10.1017/9781009093057