ECE 594: Convex Optimization (Fall 2021)

Lectures

Mon/Wed, 4:30-5:45pm, Lecture Center A7

Instructor

Shuo Han (hanshuo@uic.edu)
Office hours: Mon, 2:30-4:00pm, 1110 SEO

Teaching Assistant

N/A

Course Description

This graduate-level course covers three main aspects of convex optimization: theory, applications (e.g., machine learning, signal/image processing, controls), and algorithms. After taking the course, students should be able to recognize convexity and use convex optimization to model and solve problems that arise in engineering applications. Students will also gain a basic understanding of how convex optimization problems are solved algorithmically so as to determine whether a given problem can be solved using off-the-shelf solvers.

Prerequisites

Good knowledge of linear algebra (e.g., as in ECE 550 or ECE 531). Exposure to probability (e.g., ECE 341). Familiarity with MATLAB.

Topics

Course Policy

Grading

Course Logistics

We will use a number of websites throughout this course, each of which has a different purpose.

Homework Policy

Collaboration

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COVID-19 Special Policies

The following policies are from the official guidance provided by the University:

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Course Text and References

The required textbooks for the course is:

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