{"product_id":"mathematical-analysis-of-machine-learning-algorithms-hardback-9781009098380","title":"Mathematical Analysis of Machine Learning Algorithms (Hardback) 9781009098380","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eMathematical Analysis of Machine Learning Algorithms\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eIntroduction to the mathematical foundation for understanding and analyzing machine learning algorithms for AI students and researchers.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eTong Zhang (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781009098380, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 10 August 2023\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e479 pages\u003cbr\u003e25.4 x 17.8 x 2.5 cm, 1.113 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e'This book gives a systematic treatment of the modern mathematical techniques that are commonly used in the design and analysis of machine learning algorithms. Written by a key contributor to the field, it is a unique resource for graduate students and researchers seeking to gain a deep understanding of the theory of machine learning.' Shai Shalev-Shwartz, Hebrew University of Jerusalem\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eThe 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.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e1. Introduction\u003cbr\u003e 2. Basic probability inequalities for sums of independent random variables\u003cbr\u003e 3. Uniform convergence and generalization analysis\u003cbr\u003e 4. Empirical covering number analysis and symmetrization\u003cbr\u003e 5. Covering number estimates\u003cbr\u003e 6. Rademacher complexity and concentration inequalities\u003cbr\u003e 7. Algorithmic stability analysis\u003cbr\u003e 8. Model selection\u003cbr\u003e 9. Analysis of kernel methods\u003cbr\u003e 10. Additive and sparse models\u003cbr\u003e 11. Analysis of neural networks\u003cbr\u003e 12. Lower bounds and minimax analysis\u003cbr\u003e 13. Probability inequalities for sequential random variables\u003cbr\u003e 14. Basic concepts of online learning\u003cbr\u003e 15. Online aggregation and second order algorithms\u003cbr\u003e 16. Multi-armed bandits\u003cbr\u003e 17. Contextual bandits\u003cbr\u003e 18. Reinforcement learning\u003cbr\u003e A. Basics of convex analysis\u003cbr\u003e B. f-Divergence of probability measures\u003cbr\u003e References\u003cbr\u003e Author index\u003cbr\u003e Subject index.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Pattern recognition [\u003ca title=\"See our other books on Pattern recognition\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Pattern%20recognition%20%5BUYQP%5D%22\"\u003eUYQP\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":46001821548824,"sku":"9781009098380","price":40.35,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/products\/9781009098380i_229763b3-95ff-4126-a5be-2c5a831dc4dd.jpg?v=1696782930","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/mathematical-analysis-of-machine-learning-algorithms-hardback-9781009098380","provider":"Freshly Printed Books","version":"1.0","type":"link"}