First-order and Stochastic Optimization Methods for Machine Learning

Name: First-order and Stochastic Optimization Methods for Machine Learning
Brand: Springer Nature Switzerland AG
SKU: 9783030395704
Price: 21600 KES
Availability: OutOfStock
ISBN: 9783030395704

2020 ed.

by Guanghui Lan

Book Details

Format Paperback / softback

Book Series Springer Series in the Data Sciences

ISBN-10 3030395707

ISBN-13 9783030395704

Edition 2020 ed.

Publisher Springer Nature Switzerland AG

Imprint Springer Nature Switzerland AG

Country of Manufacture GB

Country of Publication GB

Publication Date May 16th, 2021

Print length 582 Pages

Weight 888 grams

Dimensions 15.50 x 23.50 x 3.50 cms

Product Classification: Optimization Machine learning

KSh 21,600.00

Currently unavailable 0 in stock

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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.

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. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.

Get First-order and Stochastic Optimization Methods for Machine Learning by Guanghui Lan at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer Nature Switzerland AG and it has 582 pages.