Stat 679A

      High-dimensional Estimation      

Fall 2013




[Syllabus] [Homework] [Announcements] [References]

Current and previous announcements:
  • Thursday, September 26
  • Tuesday, September 24

    People

    Professor:
    Sahand Negahban (sahand dot negahban at yale dot edu)
    Office: 24 Hillhouse Rm. 207
    Office hours: Wednesday, 1:15-2:30 (Location at 24 Hillhouse Rm. 207)

    Practical information

    Course description: In this course we will review the recent advances in high-dimensional statistics. We will cover concepts in empirical process theory, concentration of measure, and random matrix theory in the context of understanding the statistical properties of high-dimensional estimation methods. In this discussion we will also overview the computational constraints that are involved with solving high-dimensional problems and touch upon concepts in convex optimization and online learning.

    Lectures: 24 Hillhouse Ave Rm 107; Tues, Thurs 12:00-1:15.

    Grading: Homework

    Required background: The prerequisites are previous coursework in linear algebra, multivariate calculus, and basic probability and statistics.

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    Last modified: Fri August, 30