High-Dimensional Statistics

Wed. 12-12:50,  Rm  Mth 0201 Fall '24
 

Eric Slud Vince Lyzinski Statistics Program , Math Department

Interested participants should get in touch with us at   slud@umd.edu, or vlyzinsk@umd.edu


Reading list

The main reference we will cover is

High-Dimensional Statistics: A Non-asymptotic Viewpoint, by Martin Wainwright, Cambridge Univ. Press 2019.

Chapters freely downloadable for students through the UMD Libraries website.

Older related statistical papers can be found in the old RIT website RIT on Statistics of Models with Increasing Parameter Dimension, F05

Other recommended books:

Boucheron, S., Lugosi, G., & Massart, P. (2013). Concentration inequalities: a non asymptotic theory of independence

-- https://www.amazon.com/Concentration-Inequalities-Nonasymptotic-Theory-Independence/dp/019876765X

Horn, Roger A., and Charles R. Johnson. Matrix analysis. Cambridge university press, 2012. -- https://www.amazon.com/Matrix-Analysis-Second-Roger-Horn/dp/0521548233


Schedule of Talks
Note: where available, links to slides are in the names and dates of past speakers

Ch.1 of Wainwright:   Shitao Fan,   Sept. 4
Ch.2 of Wainwright:   Tail inequality material involving sub-Gaussian, sub-exponential (Sec.2.1),   Nick Wu, Sept. 11
Ch.3 on Concentration of Measure,   Vince Lyzinski, Sept. 18
Ch.2 of Wainwright, martingale material (Sec.2.2 + background) Eric Slud, Sept.25
Ch.7 on Sparse Linear Models (with some Lasso background),   Chugang Yi, Oct. 2 & 9
Ch.4 of Wainwright, Uniform Laws of Large Numbers and Rademacher Complexity,   Perrin Ruth, Oct. 16
Ch.5 on Metric Entropy and Gaussian processes,   Willie Dong, Oct. 23
Metric entropy was covered on Oct. 23; some material on Gaussian processes from Secs. 5.2-5.3
will be covered in the first half of the RIT meeting on Oct.30

We may continue to spill over in covering chapters across successive weeks.

Ch.8 on Principal Component Analysis,   John McMenimon, October 30 and November 6
Ch.6 on Random Matrices and Covariance Estimation: James Kwon, began on Nov.6, resumed Nov.13
Ch.10 on Matrix Estimation with Rank Constraints,   Zhirui Li, November 20
Ch.11 on Graphical Models,   Kartik Ravisankar, December 4



Topics & Papers

Here is a link to a recommended paper on The Blessings of Dimensionality.


EVS home page.


© Eric V Slud, November 11, 2024.