Algorithmic Foundations of Data Science
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David Steurer
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Spring Semester
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Location: rack 8, shelf 1
This course provides rigorous theoretical foundations for the design and mathematical analysis of efficient algorithms that can solve fundamental tasks relevant to data science.
AVAILABLE
READING ROOM ONLY
NOT AVAILABLE
ONLINE VERSION
High-dimensional statisticsA non-asymptotic viewpoint Martin J. Wainwright (University of California, Berkeley)
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AVAILABLE
READING ROOM ONLY
NOT AVAILABLE
ONLINE VERSION
Algorithmic aspects of machine learningAnkur Moitra, Massachusetts Institute of Technology
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AVAILABLE
READING ROOM ONLY
NOT AVAILABLE
ONLINE VERSION
High-dimensional probabilityAn introduction with applications in data science Roman Vershynin (University of California, Irvine)
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AVAILABLE
ONLINE VERSION