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Material Detail

18.409 Algorithmic Aspects of Machine Learning | Mathematics

18.409 Algorithmic Aspects of Machine Learning | Mathematics

This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze for fundamental machine learning problems.... Show More
Keywords:
matrix completion, learning mixture model, sparse recovery, nonnegative matrix factorization, Theory of Computation, sparse coding, Discrete Mathematics, tensor rank, Algorithms and Data Structures, Machine learning, border rank, tensor decomposition, Applied Mathematics
Disciplines:
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More about this material

Material Type:
Online Course
Date Added to MERLOT:
May 12, 2016
Date Modified in MERLOT:
May 12, 2016
Author:
Unknown (Know the author?)
Submitter:
Barbra Bied Sperling
Hispanic Serving Institution
Primary Audience:
Graduate School
Technical Format:
Website
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Accessibility Information Available:
Unknown
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States

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