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.
General
Imprint: |
Cambridge UniversityPress
|
Country of origin: |
United Kingdom |
Release date: |
July 2023 |
Authors: |
Tong Zhang
|
Pages: |
479 |
ISBN-13: |
978-1-00-909838-0 |
Categories: |
Books
|
LSN: |
1-00-909838-1 |
Barcode: |
9781009098380 |
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