ELE538B: Sparsity, Structure and Inference

Yuxin Chen, Princeton University, Spring 2017

Instructor

  • Yuxin Chen, C330 Equad, yuxin dot chen at princeton dot edu

  • Office hours: Mon/Wed 11am - 12pm (after the lectures), C330 Equad, or by appointment

Teaching Assistant

  • Yeohee Im, F210-E3 Equad (email: yeoheei at princeton dot edu)

  • Office hours: Tue 4:30-5:30pm, F210-E3 Equad, or by appointment

Lecture Times

  • Mon, Wed 9:30 AM - 10:50 AM

Location

Administrative Assistant

Assessment

  • Homeworks (40%). There will be a few homework assignments that involve both theory and programming components. A hard copy of your homework must be turned in at the beginning of class. No late homeworks are accepted. You are encouraged to use LaTeX to typeset your homeworks.

  • Final project (60%). See the description here.

Review sessions

There will be a few review sessions given at the beginning of the semester. The purpose of the sessions is to give you a quick review of basic linear algebra and probability. Attendance is optional.

Course Policies

  • Prerequisites. Students should have backgrounds in basic linear algebra and in basic probability (measure- theoretic probability is not needed), as well as knowledge of a programming language like MATLAB or Python to conduct simple simulation exercises. While no specific background in optimization is required, a course such as ORF307 (Optimization) would be beneficial.

  • Piazza. The main mode of electronic communication between students and staff, as well as amongst students, will be through http:www.piazza.com/. It is intended for general questions about the course, clarifications about assignments, student questions to each other, discussions about material, and so on. We strongly encourage students to participate in discussion, ask and answer questions through this site. The course staff will monitor discussions closely.

  • Collaboration. We encourage you to work on homework problems in study groups. However, you must write up and submit your own solutions and code without reading or copying the solutions of other students or other online resources.