Information

  • Instructor: Lu Wang
  • Time/Location: Tue 8:00-9:40am, C-402; Thu 8:00-9:40am, C-402
  • TA: Zhuan Zhang (zhangzhuan@csu.edu.cn), Zhenyuan Shen (shenzhenyuan@csu.edu.cn)
  • Syllabus

Schedule

Date   Lecture   Homework   Due  
02/26   generate uniform random variables          
02/28   generate non-uniform random variables   Homework 1
rmarkdown_template, cdc.RData
  03/14  
03/05   truncated distributions, Box-Muller, order statistics          
03/07   bootstrap, acceptance-rejection sampling          
03/12   sample from Gamma distributions and mixture distributions          
03/14   generate random vectors          
03/19   copula-marginal method   Homework 2 - Q1   04/04  
03/21   generate random points on unit sphere, random matrices          
03/26   sample from Wishart and inverse Wishart distribution          
03/28   generate random graphs   Homework 2 - Q2   04/04  
04/02   generate random process   Homework 3   04/11  
04/04   Brownian bridge, geometric Brownian motion, Poisson point process          
04/09   Dirichlet process          
04/11   Gibbs sampler          
04/16   Metropolis-Hastings algorithm          
04/18   Hamiltonian monte carlo          
04/23   sequential monte carlo, EM algorithm   Homework 4   05/09  
04/25   gradient descent          
04/28   newton-raphson   Homework 5
facerecognition.RData
  05/09  
04/30   coordinate descent          
05/07   convex optimization          
05/09   support vector machine          
05/14   deep learning [          
05/16   summary   Some datasets for course paper:
epigen.dat description
springbok.xls description
IrishElectricity.txt description
  06/16  

Evaluation

  • 10% Class participation
  • 40% Homework
  • 50% Course project paper (requirements)
  • Late work will be penalized 25% per day
  • You may help each other on homework, but the work you turn in must be your own.