ISyE 6416: Computational Statistics

Prof. Yao Xie, Georgia Tech, Spring 2016

Computational statistics is an interface between statistics and computing. We will cover algorithms arising from parametric and nonparametric statistical problems, developed with optimization and other modern computational tools. Course will cover the following topics:

  • Basics of algorithm and optimization
  • Classification and clustering
  • EM algorithm
  • Gaussian mixture model (GMM)
  • Hidden Markov models (HMM)
  • Model selection and cross validation
  • Splines
  • Principle component analysis
  • Bootstrap
  • Monte Carlo methods

    • Course info

  • Instructor: Prof. Yao Xie. Email: yao.xie@isye.gatech.edu. Office Hour: Wed 1-2pm, Groseclose 339.

  • Schedule: Tuesday, Thursday, 12:05-1:25pm. Room: Clough 102.

  • Syllabus

    • Lectures

    1. Introduction

    2. Aspects of algorithms

    3. Basics of statistical inference

    4. Gradient descent and Newton's method

    5. Classification

    6. Clustering

    7. EM algorithm

    8. Hidden Markov model

    9. Model Selection

    10. Spline

    11. Principal component analysis

    12. Bootstrap

    13. Monte Carlo methods

    14. Markov Chain Monte Carlo