Tong Zhang (Hong Kong University of Science and Technology)

Mathematical Analysis of Machine Learning Algorithms

• Gebundenes Buch

Produktbeschreibung

This self-contained textbook introduces students and researchers of AI to the key mathematical concepts and techniques necessary to learn and analyze machine learning algorithms. Readers will gain the technical knowledge needed to understand research papers in theoretical machine learning, without much difficulty.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 479
• Erscheinungstermin: 10. August 2023
• Englisch
• Abmessung: 256mm x 180mm x 28mm
• Gewicht: 1062g
• ISBN-13: 9781009098380
• ISBN-10: 1009098381
• Artikelnr.: 67636842

Autorenporträt

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.'

Inhaltsangabe

1. Introduction
2. Basic probability inequalities for sums of independent random variables
3. Uniform convergence and generalization analysis
4. Empirical covering number analysis and symmetrization
5. Covering number estimates
6. Rademacher complexity and concentration inequalities
7. Algorithmic stability analysis
8. Model selection
9. Analysis of kernel methods
10. Additive and sparse models
11. Analysis of neural networks
12. Lower bounds and minimax analysis
13. Probability inequalities for sequential random variables
14. Basic concepts of online learning
15. Online aggregation and second order algorithms
16. Multi-armed bandits
17. Contextual bandits
18. Reinforcement learning
A. Basics of convex analysis
B. f-Divergence of probability measures
References
Author index
Subject index.