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Learning Theory from First Principles - FRANCIS BACH

Learning Theory from First Principles

FRANCIS BACH

 
99,00 $

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EN SAVOIR PLUS Résumé

A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory.

Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. . In this accessible textbook, Francis Bach presents the foundations and latest advances of learning theory for graduate students as well as researchers who want to acquire a basic mathematical understanding of the most widely used machine learning architectures. Taking the position that learning theory does not exist outside of algorithms that can be run in practice, this book focuses on the theoretical analysis of learning algorithms as it relates to their practical performance. Bach provides the simplest formulations that can be derived from first principles, constructing mathematically rigorous results and proofs without overwhelming students.

Provides a balanced and unified treatment of most prevalent machine learning methods

Emphasizes practical application and features only commonly used algorithmic frameworks
Covers modern topics not found in existing texts, such as overparameterized models and structured prediction
Integrates coverage of statistical theory, optimization theory, and approximation theory
Focuses on adaptivity, allowing distinctions between various learning techniques
Hands-on experiments, illustrative examples, and accompanying code link theoretical guarantees to practical behaviors


Détails
Prix : 99,00 $
Catégorie :
Auteur :  FRANCIS BACH
Titre : Learning Theory from First Principles
Date de parution : 24 décembre 2024
Éditeur : MIT PRESS
Pages : 478
Sujet : Général
ISBN : 9780262049443 (0262049449)
Référence Renaud-Bray : 20123862
No de produit : 4212417

Learning Theory from First Principles , BACH, FRANCIS
© MIT PRESS 2024
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