MATH 7740
Last Updated
- Schedule of Classes - December 22, 2024 7:33PM EST
- Course Catalog - December 22, 2024 7:07PM EST
Classes
MATH 7740
Course Description
Course information provided by the Courses of Study 2024-2025.
Learning theory has become an important topic in modern statistics. This course gives an overview of various topics in classification, starting with Stone's (1977) stunning result that there are classifiers that are universally consistent. Other topics include classification, plug-in methods (k-nearest neighbors), reject option, empirical risk minimization, Vapnik-Chervonenkis theory, fast rates via Mammen and Tsybakov's margin condition, convex majorizing loss functions, RKHS methods, support vector machines, lasso type estimators, low-rank multivariate response regression, random matrix theory, topic models, latent factor models, and interpolation methods in high dimensional statistics.
When Offered Fall.
Permission Note Enrollment limited to: graduate students.
Prerequisites/Corequisites Prerequisite: basic mathematical statistics (STSCI 6730/MATH 6730 or equivalent) and measure theoretic probability (MATH 6710), or permission of instructor.
Regular Academic Session.
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Credits and Grading Basis
3 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- MW Malott Hall 205
- Aug 26 - Dec 9, 2024
Instructors
Wegkamp, M
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Additional Information
Instruction Mode: In Person
Enrollment limited to: graduate and professional students.
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