Bokus
Tong Zhang - Mathematical Analysis of Machine Learning Algorithms, Inbunden

Inbunden, Engelska, 2023

Mathematical Analysis of Machine Learning Algorithms

Av Tong Zhang

790 kr

Beställningsvara. Skickas inom 3-6 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

Beskrivning
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.
Produktinformation
  • Utgivningsdatum: 2023-08-10
  • Mått: 185 x 263 x 30 mm
  • Vikt: 1 050 g
  • Format: Inbunden
  • Språk: Engelska
  • Antal sidor: 468
  • Förlag: Cambridge University Press
  • ISBN: 9781009098380
Utforska kategorier
Mer om författaren

Tong Zhang is Chair Professor of Computer Science and Mathematics at the Hong Kong University of Science and Technology, where his research focuses on machine learning, big data, and their applications. A Fellow of the IEEE, the American Statistical Association, and the Institute of Mathematical Statistics, Zhang has served as Chair or Area chair at major machine learning conferences such as NeurIPS, ICML, and COLT, and he has been an associate editor for several top machine learning publications including PAMI, JMLR, and 'Machine Learning.'

Recensioner i media

'This graduate-level text gives a thorough, rigorous and up-to-date treatment of the main mathematical tools that have been developed for the analysis and design of machine learning methods. It is ideal for a graduate class, and the exercises at the end of each chapter make it suitable for self-study. An excellent addition to the literature from one of the leading researchers in this area, it is sure to become a classic.' Peter Bartlett, University of California, Berkeley

Betyg & recensioner

0 recensioner

Inga recensioner tillgängliga.