Algorithms for Convex Optimization (Cambridge University Press)
Friday, 08 October 2021

This book looks at how algorithms for convex optimization have become important in algorithm design for both discrete and continuous optimization problems. Nisheeth K. Vishnoi considers their use for problems like maximum flow, maximum matching, and submodular function minimization, and shows how the fastest algorithms involve essential methods such as gradient descent, mirror descent, interior point methods, and ellipsoid methods.

<ASIN:1108741770>

The aim is to enable researchers and professionals in computer science, data science, and machine learning to gain an in-depth understanding of these algorithms. The text emphasizes how to derive key algorithms for convex optimization from first principles and how to establish precise running time bounds.

Author: Nisheeth K. Vishnoi
Publisher: Cambridge University Press
Date: October 2021
Pages: 340
ISBN: 978-1108741774
Print: 1108741770
Kindle: B09D419HJB
Audience: General
Level: Intermediate/Advanced
Category: Theory & Techniques 

 

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Publisher: O'Reilly
Date: February 2020
Pages: 166
ISBN: 978-1492075332
Print: 1492075337
Kindle: B084D653HW
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Rating: 2
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Date: December 2019
Pages: 770
ISBN: 978-1789955750
Print: 1789955750
Kindle: B07VBLX2W7
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Rating: 5
Reviewer: Mike James
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