Teaching

High Dimensional Statistics

The course presents an introduction to modern statistical and probabilistic methods for data analysis, emphasising finite sample guarantees and problems arising from high-dimensional data. The course is mathematically oriented and level of the material ranges from a solid undergraduate to a graduate level. Topics studied include for instance Concentration Inequalities, High Dimensional Linear Regression and Matrix estimation.

Lectures:

  • Lecture 1. Preliminaries on concentration and suprema of random variables pdf
  • Lecture 2. The LASSO for high-dimensional linear regression pdf

References for the course:

Optimal Transport

This course is an introduction to the theory of Optimal Transport, aiming at presenting some of the basic results in the field. The course is offered as an elective course in several Master and PhD programs at HSE University. Prerequisites for the course include a basic knowledge of Differential Calculus, Convex analysis, Measure Theory and Topology.

Lectures:

  • Lecture 1. The optimal transport problem pdf
  • Lecture 2. Existence of optimal transport plans pdf
  • Lecture 3. Kantorovich-Wasserstein distances pdf
  • Lecture 4. Necessary and sufficient optimality conditions pdf
  • Lecture 5. Duality and existence of optimal transport maps pdf
  • Lecture 6. Continuity equation pdf
  • Lecture 7. The formal Riemannian structure of W_2 pdf

References for the course: