MIT Subject Listing & Schedule
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Searched for: "15.095"    Subjects offered any term

1 subject found.

15.095 Machine Learning Under a Modern Optimization Lens
(New)

(, )
Prereq: 6.251, 15.093, or permission of instructor
Units: 3-1-8
Lecture: MW4-5.30 (E51-315) Recitation: F10.30 (E51-335)

Develops algorithms for central problems in machine learning from a modern optimization perspective. Topics include sparse, convex, robust and median regression; an algorithmic framework for regression; optimal classification and regression trees, and their relationship with neural networks; how to transform predictive algorithms to prescriptive algorithms; optimal prescriptive trees; and robust classification. Also covers design of experiments, missing data imputations, mixture of Gaussian models, exact bootstrap, and sparse matrix estimation, including principal component analysis, factor analysis, inverse co-variance matrix estimation, and matrix completion.
D. Bertsimas
No textbook information available