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Introduction to Online Convex Optimization, second edition - ELAD HAZAN

Introduction to Online Convex Optimization, second edition

ELAD HAZAN

 
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EN SAVOIR PLUS Résumé

New edition of a graduate-level textbook on that focuses on online convex optimization, a machine learning framework that views optimization as a process.

In many practical applications, the environment is so complex that it is not feasible to lay out a comprehensive theoretical model and use classical algorithmic theory and/or mathematical optimization. Introduction to Online Convex Optimization presents a robust machine learning approach that contains elements of mathematical optimization, game theory, and learning theory: an optimization method that learns from experience as more aspects of the problem are observed. This view of optimization as a process has led to some spectacular successes in modeling and systems that have become part of our daily lives.

Based on the “Theoretical Machine Learning” course taught by the author at Princeton University, the second edition of this widely used graduate level text features:

Thoroughly updated material throughout
New chapters on boosting, adaptive regret, and approachability and expanded exposition on optimization
Examples of applications, including prediction from expert advice, portfolio selection, matrix completion and recommendation systems, SVM training, offered throughout
Exercises that guide students in completing parts of proofs


Détails
Prix : 79,00 $
Catégorie :
Auteur :  ELAD HAZAN
Titre : Introduction to Online Convex Optimization, second edition
Date de parution : 11 octobre 2022
Éditeur : MIT PRESS
Pages : 248
Sujet : Général
ISBN : 9780262046985 (0262046989)
Référence Renaud-Bray : 17959183
No de produit : 3708665

Introduction to Online Convex Optimization, second edition , HAZAN, ELAD
© MIT PRESS 2022
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