ECE 598IS - Information Theory and High-Dimensional Statistics (Fall 2025)

• Each student will be expected to be a scribe for at least one lecture.
• You can sign up for a lecture here
• Scribe Latex template
• The scribe is due one week after the lecture

Lecture notes

• Handwritten lecture notes can be found here.

Scribe notes

• Lecture 2 - Statistical Decision Theory (scribe)
• Lecture 3 - From Estimation to Testing (scribe)
• Lecture 4 - Divergence Measures and Inequalities (scribe)
• Lecture 5 - Minimax lower bound via divergence measures (scribe)
• Lecture 6 - Information Measures and Inequalities (scribe)
• Lecture 7 - Distance-based Fano's method and sparse GLM (scribe)
• Lecture 8 - Upper bound for k-sparse GLM (scribe)
• Lecture 9 - Some concentration inequalities (scribe)
• Lecture 10 - Minimax bounds for sparse linear regression (scribe)
• Lecture 11 - Spase linear regression: MLE and Lasso (scribe)
• Lecture 12 - Analysis of the Lasso (scribe)
• Lecture 13 - Linear Algebra Review (scribe)
• Lecture 14 - Eigenvalue Perturbation (scribe)