Mathematical Analysis of Machine Learning Algorithms

Thong Zhang

ISBN 10: 1009098381 / ISBN 13: 9781009098380

Editore: Cambridge University Pr. Aug 2023, 2023

Riguardo questo articolo

Neuware -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.

Codice articolo 9781009098380

Dati bibliografici

• Titolo: Mathematical Analysis of Machine Learning Algorithms
• Editore: Cambridge University Pr. Aug 2023
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 1009098381
• ISBN 13: 9781009098380
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 256 L x 180 A x 28 P (millimetri) 256 millimetri di larghezza per 180 millimetri di altezza per 28 millimetri di profondità
• Peso: 1122 grammi

Descrizione articolo

Riassunto

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.