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Algorithmic Aspects of Machine Learning

In this book, we will tackle the problem of providing testable guarantees for machine learning by trying to find more realistic models for our data. In many applications, there are reasonable assumptions we can make based on the context in which the problem arose, which can circumvent these worst case impediments and allow us to rigorously analyze the heuristics used in practice, as well as design fundamentally. new ways to solve some of the central and recurring problems in machine learning.

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Book Description:

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

About Author

Ankur Moitra has been an Associate Professor of Mathematics in the Department of Mathematics of the Massachusetts Institute of Technology since July 2017. She received the professorship in July 2019. She holds the B.S. in electrical and computer engineering from Cornell in 2007. He completed his M.S. and PhD from MIT in computer science in 2009 and 2011 respectively, where he mentored Tom Leighton and supported by a fellowship from the Fannie and John Hertz Foundation. He received a George M. Sprowls Award (best thesis) and William A. Martin Award (best thesis) for his doctoral and master’s theses.


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Algorithmic Aspects of Machine Learning

Author(s): Ankur Moitra

Publisher: Cambridge University Press, Year: 2018

ISBN: 1316636003, 978-1316636008

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