STSCI 6940

STSCI 6940

Course information provided by the Courses of Study 2022-2023.

Topics are arranged at the beginning of the semester for individual study or for group discussions. Or, students may elect to undertake a project in statistics. The work is supervised by a professor in this subject area.

When Offered Fall, Spring.

Prerequisites/Corequisites Prerequisite: MATH 6710.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • Topic: Inference and Interpretation in Machine Learning

  •  9600 STSCI 6940   LEC 001

  • Instruction Mode: In Person
    Course will cover methods for interpretation and statistical inference for machine learning methods. Topics include interpretation methods: approximation by interpretable models, functional ANOVA, LIME, Shapley values and counterfactuals. Uncertainty quantification will be studied for ensemble methods, the infinitesimal jacknife, targeted maximum likelihood methods and Bayesian methods. Class will be a mixture of lectures and papers presented by students.

Syllabi: none
  •   Seven Week - First. 

  • 1 Credit Sat/Unsat

  • Topic: Statistical Optimal Transport for High Dim Mixture

  • 18955 STSCI 6940   LEC 002

  • Instruction Mode: In Person
    Enrollment is restricted to graduate students only.