ECE 830 Statistical Signal Processing and Learning Theory   2015 Spring Semester
Open to all students with a basic background in signal processing, probability,
statistics, and linear algebra.

Robert Nowak

University of Wisconsin-Madison
Office: 3539 Engineering Hall

Monday and Wednesday, 11am-12:15pm, 3534 Engineering Hall

Office Hours:
Monday, 12:15-1:15pm (3534 EH)
Wednesday, 1:30-2:30pm (Wisconsin Institute for Discovery, 3rd floor teaching lab)

Grading and Exams:
20% HW and participation
20% Midterm Exam 1, TBA
20% Midterm Exam 2, TBA
40% Final Exam, TBA

Lecture 1
Lecture 2 (notes on concentration inequalities)
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Lecture 9
Lecture 10
Lecture 11
Lecture 12
Lecture 13
Lecture 14 (notes on generalized linear models)
Lecture 15
Lecture 16
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21
(additional notes on lasso)
Lecture 22
Lecture 23
Lecture 24
Lecture 25
Lecture 26
Lecture 27
notes on graphical models

Matlab, Matlab Tutorial

Additional Resources: Statistical Signal Processing (Scharf), Fundamentals of Statistical Signal Processing (Kay),
A Wavelet Tour of Signal Processing (Mallat), Pattern Recognition and Machine Learning (Bishop),
A Probabilistic Theory of Pattern Recognition (Devroye, Gyorfi, and Lugosi), Elements of Statistical Learning (Hastie, Tibshirani, and Friedman)