Computational and Inferential Methods for High Dimensions and Massive Datasets (Spring 2013)


Course Day and Time: Course was held at SAMSI in RTP on Tuesdays, 4:30-7:00 p.m. in Room 150.
First class Tuesday, January 8, 2013 – last class day, Tuesday, April 16, 2013.

Course Description: This course focused on fundamental methodological questions of statistics, mathematics and computer science posed by massive datasets, with applications to astronomy, high energy physics, and the environment.

Topics included:

  • Data: storage and transfer of massive datasets, missing and noisy data, complex data structures
  • Computing: efficient computational algorithms, simulation
  • Visualization: data visualization to enhance human understanding
  • Statistical Inference: problems and opportunities in high dimensional data; false discovery rates; regularization, Bayes and empirical Bayes; parametric, semi-parametric and non- parametric modeling; leveraging algorithms and computer resources

Registration for this course is processed through your respective university:

  • Duke: STA 790.01
  • NCSU: MA 810.002 and ST 810.010
  • UNC:STOR 892.1

Questions: email