Non Convex Optimization For Machine Learning
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Language: en
Pages: 218
Pages: 218
Type: BOOK - Published: 2017-12-04 - Publisher: Foundations and Trends in Machine Learning
Non-convex Optimization for Machine Learning takes an in-depth look at the basics of non-convex optimization with applications to machine learning. It introduce
Language: en
Pages: 142
Pages: 142
Type: BOOK - Published: 2015-11-12 - Publisher: Foundations and Trends (R) in Machine Learning
This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. It begins with the fundamental theory of black-b
Language: en
Pages: 591
Pages: 591
Type: BOOK - Published: 2020-05-15 - Publisher: Springer Nature
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.
Language: en
Pages: 509
Pages: 509
Type: BOOK - Published: 2012 - Publisher: MIT Press
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay betw
Language: en
Pages: 286
Pages: 286
Type: BOOK - Published: 2020-05-29 - Publisher: Springer Nature
This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problem