ECE598YW: Information-theoretic methods in high-dimensional statistics

Yihong Wu, University of Illinois, Spring 2016

The interplay between information theory and statistics is a constant theme in the development of both fields. This course will discuss how techniques rooted in information theory play a key role in understanding the fundamental limits of high-dimensional statistical problems in terms of minimax risk and sample complexity. In particular, we will rigorously justify the phenomena of dimensionality reduction by either intrinsic low-dimensionality (sparsity, smoothness, shape, etc) or - the less familiar - extrinsic low-dimensionality (functional estimation). Complementing this objective of understanding the fundamental limits, another significant direction is to develop computationally efficient procedures that attain the statistical optimality, or to understand the lack thereof.

  • Lectures: Tuesday and Thursday at 330pm–450pm in 3015 ECEB

  • Office hours: Tuesday at 11am–12pm in 129 CSL or by appointment

  • Syllabus


  • Lecture 1 has been posted.

  • Lectures on Feb 2 and Feb 4 are cancelled. Make-up lecture: Feb 8 Monday 7pm at ECEB 3015.

  • Welcome to ECE598YW Spring 2016. The first lecture is Jan 19.