Description: Statistical learning theory is a burgeoning research field at the intersection of probability, statistics, computer science, and optimization that studies the performance of computer algorithms for making predictions on the basis of training data. The following topics will be covered: basics of statistical decision theory; concentration inequalities; supervised and unsupervised learning; empirical risk minimization; complexity-regularized estimation; generalization bounds for learning algorithms; VC dimension and Rademacher complexities; minimax lower bounds; online learning and optimization. Along with the general theory, we will discuss a number of applications of statistical learning theory to signal processing, information theory, and adaptive control.
Problem sets:
Problem set 1 .tex
Exams:
Exam 1, Wednesday, March 6, 7-9 pm, 2013 ECEB
Exam 2, Tuesday, April 30, 7-9 pm, 2013 ECEB
Grading scheme: Homework, six problem sets (30%), two midterm exams (25% each), project (20%).
Prerequisite: ECE 534, Random Processes
Credit: 4 graduate hours
Lecture times and location: TuTh 2:00-3:20 p.m. in Room 2015 ECE Building
Lecture schedule: schedule of lectures lecture capture
Assigned Reading: The reading will mainly be from notes prepared for this course. These notes will be updated throughout the semester so it is not recommended that you print them all out. See the Fall 2013, Fall 2014, Fall 2015, Spring 2017 , and Spring 2018 websites for earlier versions of the course. Additional reading may be assigned from other books or articles, including:
Course Staff and Office Hours:
Bruce Hajek, Instructor
b-hajek AT illinois dot edu |
Office Hours: Wednesdays, 1-2:30 pm in Room 105 CSL |
Bolton Bailey, TA boltonb2 AT illinois dot edu |
Office Hours: Mondays, 3-4 pm in Room 4034 ECEB |
Zeyu Zhou, TA zzhou51 AT illinois dot edu |
Office Hours: Mondays, 5-6 pm in Room 4034 ECEB |
Optional recitation sessions. Staffed by TAs. |
Fridays, 1pm-2pm in Room 3020 ECEB (north tower)
TAs will work out sample problems and examples, review background material as needed. |
Question and answer site: Piazza
About the project: For the project you are to choose a topic related to the course content and understand and critically evaluate two or three major papers in that area. Then demonstrate knowledge of the papers by working an example based on a paper or possibly extending the theory of a paper. You will need to write a project report of five to ten pages in length, and prepare a fifteen minute presentation.
Additional policy:
Collaboration on the homework is permitted, however each student must write and submit independent solutions. That means working out the final details, the presentation, and wording in the homework solutions on your own. Homework is due within the first 5 minutes of the class period on the due date. No late homework will be accepted (unless an extension is granted in advance by the instructor).
You are encouraged to do
your homework in Latex. The .tex source of the problem set is provided for your convenience. Also, you can upload
your homework to the compass/blackboard system instead of turning in a hard copy. If your
solutions are hand written, points may be deducted if the handwriting is difficult to read.
You may bring one sheet of notes to the first exam and two sheets of notes to the second exam. You may use both sides of the sheets,
with font size 10 or larger printing (or similar handwriting size). The examinations are closed book otherwise. Calculators, laptop
computers, tables of integrals, etc. are not permitted.