Mathematical Methods of Data Theory

Lecture, three hours; discussion, one hour. Requisites: courses 42, 115A. Introduction to computational methods for data problems with focus on linear algebra and optimization. Matrix and tensor factorization, PageRank, assorted other topics in matrices, linear programming, unconstrained optimization, constrained optimization, integer optimization, dynamic programming, and stochastic optimization. P/NP or letter grading.

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Course

Instructor
Daniel McKenzie
Previously taught
21F 20F 20W