CS 686 - Introduction to Convex Optimization

(3 units)

This course will introduce basic concepts of convex optimization and algorithms for convex optimization (e.g., Newton’s method, gradient descent methods). We will concentrate on recognizing and solving convex optimization problems that arise in engineering applications. This course would benefit anyone who uses or will use scientific computing or optimization in engineering or related work (e.g., machine learning, robotics, computer graphics, algorithms & complexity, computational geometry).

Maximum units a student may earn: 3

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
2. apply computer science theory and software development fundamentals to produce computing-based solutions.
3. apply engineering and computer science research and theory to advance the art, science, and practice of the discipline.

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