TY - BOOK ID - 145649102 TI - Mathematical analysis of machine learning algorithms PY - 2023 SN - 1009115553 1009093053 9781009115551 9781009093057 9781009098380 PB - Cambridge, United Kingdom ;New York, NY Cambridge University Press DB - UniCat KW - Machine learning KW - Artificial intelligence KW - Mathematics UR - https://www.unicat.be/uniCat?func=search&query=sysid:145649102 AB - 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. ER -