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Book Cover
E-book
Author Lin, Zhouchen.

Title Accelerated optimization for machine learning : first-order algorithms / Zhouchen Lin, Huan Li, Cong Fang
Published Singapore : Springer, 2020

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Description 1 online resource
Contents Introduction -- Accelerated algorithms for unconstrained convex optimization -- Accelerated algorithms for constrained convex optimization -- Accelerated algorithms for nonconvex optimization -- Accelerated stochastic algorithms -- Accelerated parallel algorithms -- Conclusions
Summary This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time. -- Provided by publisher
Bibliography Includes bibliographical references and index
Subject Machine learning -- Mathematics
Mathematical optimization.
Optimization.
Maths for computer scientists.
Numerical analysis.
Machine learning.
Mathematics -- Applied.
Computers -- Data Processing.
Mathematics -- Counting & Numeration.
Computers -- Intelligence (AI) & Semantics.
Mathematical optimization
Form Electronic book
Author Li, Huan
Fang, Cong
ISBN 9789811529108
9811529108