Algorithmic Aspects of Machine Learning (Ankur Moitra)

 
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Algorithmic Aspects of Machine Learning (Ankur Moitra)

This book examines how theoretical computer science and machine learning can complement one another. It highlights the need for adaptable, manageable models that better capture what makes machine learning simple rather than difficult.

The basic issues in the field of machine learning and key models will be introduced to theoretical computer scientists. Researchers in machine learning will become acquainted with a contemporary algorithmic toolset, including the method of moments, tensor decompositions, and convex programming relaxations, and will be introduced to cutting-edge research in an approachable way.

Beyond a worst-case scenario analysis, the goal is to develop a solid understanding of the methodologies used in practice and to make it easier to find novel, exciting solutions to significant, old problems.

Ebook Details

Author(s)
About the Authors
At Massachusetts Institute of Technology, Ankur Moitra teaches mathematics as the Rockwell International Associate Professor. He is a fundamental member of the Theory of Computation Group, Machine Learning@MIT, the Center for Statistics, and the Computer Science and Artificial Intelligence Lab (CSAIL).
Published
Published Date / Year
(2018); eBook (Draft for Version 2)
Hardcover
158 pages
eBook Format
PDF (249 pages)
Language
English
ISBN-10
1316636003
ISBN-13
978-1316636008

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