Reading material for the class will be assigned from:

36-755, Fall 2016
Class Schedule
Date Lecture Topic Readings Scribe Notes Notes
Aug 28, M Introduction: high-dimensional statistical models
  • [W] Chapter 1
Aug 30, M Sub-Gaussian variables
  • [W] 2.1.1, 2.1.2.
pdf
Sep 6, W Sub-Gaussian variables. Hoeffding bounds and sharpening. Sub-exponential variables.
  • [W] 2.1.2, 2.1.3
pdf HW1 is out. Solutions
Sep 11, M Sub-exponential variables, Bernstein inequality, expected value of maxima.
  • [W] 2.1.3, 2.1.4
pdf
Sep 13, W The bounded difference inequality and applications.
  • [W] 2.2
pdf
Sep 18, M Concentration of Lipschitz functions of Gaussian vectors. Covering and Packing numbers.
  • [W] 2.3, 5.1
pdf
Sep 20, W Discretization argument. Review of matrix alegbra. Estimation of the covriance matrix in operator norm.
  • [W] 6.1, 6.3
pdf HW2 is out. Solutions
Sep 25, M Matrix Calculus and Matrix Bernetsin Inequality
  • [W] 6.4
pdf
Sep 27, W Matrix Bernstein Inequality and application to covariance matrix estimation.
  • [W] 6.4
pdf
Oct 2, M Matrix Bernstein Inequality and its use in network community recovery. Linear regression.
  • [W] 6.4
pdf
Oct 4, W Finite sample performance for Linear regression. Penalized regression.
  • [W] 71., 7.3
pdf HW3 is out. Solutions
Oct 9, M Slow rate for the LASSO. The RE condition.
  • [W] 71., 7.3
pdf
Oct 11, W More on ridge regression and thresholding estimation. Fast rates for the lasso.
  • [W] 7.3
pdf
Oct 16, M Oracle inequalities for least squares and the lasso.
  • [W] 7.3
pdf
Oct 18, W Persistence. Intro to PCA.
  • Greenshtein and Ritov (2004) and [W] 8.1
pdf HW4 is out. Solutions
Oct 23, M Distance between linear sub-spaces and Davis Kahan theorem.
  • [W] 8.1, 8.2
pdf
Oct 25, W PCA in high-dimensions. Spiked covariance model. Sparse PCA.
  • [W] 8.2, 8.3
pdf
Oct 30, M Sparse PCA. Spectral clustering for SBMs. pdf
Nov 1, W Uniform law of larger numbers. Symmetrization Lemma.
  • [W] 4.1, 4.2
HW5 is out. Solutions
Nov 6, M No Class.
Nov 8, W Uniform law of larger numbers. Symmetrization Lemma.
  • [W] 4.1, 4.2
pdf
Nov 13, M VC theory.
  • [W] 4.2, 4.3
pdf
Nov 15, W VC theory for functions.
  • [W] 4.3
pdf
Nov 20, M Maximal Inequalities for Sub-Gaussian Processes.
  • [W] 5.2, 5.3
pdf
Nov 27, M Chaining and Dudley's entropy integral.
  • [W] 5.4



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