Consultation hours

##### Friday

##### From 14:00 to 18:00

##### Office S 943 on Pokrovsky campus

##### For another appointment, contact me by email at qparis@hse.ru

Current courses

##### Topics in High-Dimensional Probability and Statistics

#####

##### Main reference:

##### R. Vershynin. High-dimensional probability. An introduction with applications in data science. Cambridge Series in Statistical and Probabilistic Mathematics. vol 47. 2018

#####

##### Journal:

##### Lecture 8:

##### High-dimensional linear regression; Lasso procedure.

##### Black board: [pdf]

##### Notes: [pdf]

#####

##### Lecture 7:

##### Stochastic bloc model; Community detection in random graphs.

##### Notes: [pdf]

#####

##### Lecture 6:

##### Matrix Bernstein inequality.

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##### Lecture 5:

##### PCA; Spiked covariance model.

#####

##### Lecture 4:

##### Johnson-Lindenstrauss lemma. Covariance matrix estimation.

##### Notes: [pdf]

#####

##### Lecture 3:

##### Suprema of sub-gaussian random variables.

##### Notes: [pdf]

#####

##### Lecture 2:

##### Generalized Hoeffding inequality for sums of independent sub-gaussian r.v.'s; Sub-exponential distributions; Bernstein inequality for sums of independent sub-exponential r.v.'s.

##### Notes: [pdf]

#####

##### Lecture 1:

##### Elementary properties of sub-gaussian distributions and in particular their concentration properties.

##### Notes: [pdf]

#####

#####

#####

##### Topics in Statistical Learning Theory

##### (Modern Methods of Decision Making)

#####

##### Main reference:

##### These lectures: (link)

##### Older lecture notes: (link)

#####

##### Journal:

#####

##### Lecture 9:

##### Mirror descent.

Time: Monday, April 6, 2020, 13:30 (Moscow)

Join Zoom Meeting: here

Meeting ID: 807 937 894

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