Concentration Inequalities: Theory and Applications

Spring 2015

Time & Location: Tue, Thu 1:30-3:00pm in JMHH F38

Instructor: Alexander Rakhlin

Course Description

Prerequisites: Probability Theory and Linear Algebra.


Suggested Readings


  • S. Boucheron, G. Lugosi, P. Massart. Concentration Inequalities: A Nonasymptotic Theory of Independence.
  • R. van Handel. Probability in High Dimension.
  • M. Ledoux. The Concentration of Measure Phenomenon.
  • J.M. Steele. Probability Theory and Combinatorial Optimization.
  • R. Vershynin. Introduction to the non-asymptotic analysis of random matrices.
  • M. Raginsky and I. Sason. Concentration of measure inequalities in information theory, communications and coding.
  • S. Chatterjee. Superconcentration and Related Topics.
  • M. Ledoux and M. Talagrand. Probability in Banach Spaces.
  • A. van der Vaart and J. Wellner. Weak Convergence and Empirical Processes: With Applications to Statistics.
  • Articles: