X2TE2109: Convex Optimization and Its Applications in Signal Processing

• Instructor: Anthony Man-Cho So (manchoso at se.cuhk.edu.hk)
• Lecture Time: Tuesdays 2:00pm - 3:40pm, Thursdays 4:00p - 5:40pm

Course Description

General References

• Ben-Tal, Nemirovski: Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering Applications, SIAM, 2001.
• Boyd, Vandenberghe: Convex Optimization, Cambridge University Press, 2004.
• Güler: Foundations of Optimization, Springer, 2010.
• Luenberger, Ye: Linear and Nonlinear Programming (4th Edition), Springer, 2016.
• Nesterov: Introductory Lectures on Convex Optimization: A Basic Course, Kluwer Academic Publishers, 2004.

Handouts

• Handout A: Linear Algebra Cheat Sheet
• Handout B: Real Analysis Cheat Sheet
  
  The mathematical prerequisites for this course are summarized in Handouts A and B. Students are strongly advised to go through them carefully.
  
  
• Handout 1: Introduction
• Handout 2: Elements of Convex Analysis
• Handout 3: Elements of Linear Programming
• Handout 4: Some Applications of Linear Programming
• Handout 5: Elements of Conic Linear Programming
• Handout 6: Quadratically Constrained Quadratic Optimization with Complex Variables and Rank Reduction in Semidefinite Programming
• Handout 7: Optimality Conditions and Lagrangian Duality

Lecture Notes

• Week 1: Lecture 1   Lecture 2
• Week 2: Lecture 3   Lecture 4
• Week 3: Lecture 5   Lecture 6
• Week 4: Lecture 7   Lecture 8
• Week 5: Lecture 9   Lecture 10
• Week 6: Lecture 11   Lecture 12
• Week 7: Lecture 13   Lecture 14
• Week 8: Lecture 15   Lecture 16
• Week 9: Lecture 17
• Week 10: Lecture 18   Lecture 19
• Week 11: Lecture 20   Lecture 21
• Week 12: Lecture 22   Lecture 23
• Week 13: Lecture 24

Homework Sets