最佳化理論與應用

This course will focus on convex optimization, which has been used in efficiently solving many signal processing and communications problems, thanks to the development of interior point method (IPM), specifically the primal-dual IP algorithm. The course will include both 1) problem modeling (formulation), i.e. recognizing if a problem is convex, and if possible, turning a seemingly non-convex problem into a convex one, and 2) learning the algorithms, mainly the IPM and its variations, that can efficiently solve the problem. We will NOT be covering integer nor mixed-integer convex programming, nor problems that involve nondifferentiable functions, which may require the use of subgradient and subgradient methods. However, individual discussions can be held based on the student’s research needs.

: Linear Algebra, Probability and Statistics. Background in Linear Programming and/or Real Analysis will helpful but not required

Course website: http://cwww.ee.nctu.edu.tw/~cfung/courses/2018_2019/optim/ TA: Mykola Servetnyk (孫麥可) Office: ED 529, 03-571-2121, ext. 54232 Office Hours: xx:xx – xx:xx, xxx or by appointment Email: rusly1994@gmail.com

-- Written Assignment (20%) -- Matlab Assignment (20%) -- Class Participation (0-10%) -- Given to students who 1) actively participate in class, for example, raising good questions, and 2) borderline in terms of grades. -- No credit will be given for simply showing up -- Midterm (30%) -- Length: 2 hour exam. -- Scope: Covers everything from beginning of the course until xxx (inclusive). -- Open textbook (Chi and Boyd), notes, and homework assignments. -- Final (30%) -- Length: 2 hour exam. -- Scope: Comprehensive. -- Open textbook, notes, and homework assignments.

-- Textbook : CONVEX OPTIMIZATION FOR SIGNAL PROCESSING AND COMMUNICATIONS, by C.-Y. Chi, W.-C. Li, and C.-H. Lin, CRC Press, 2017. - Selected topics from Ch. 1-10 will be covered. CONVEX OPTIMIZATION, by S. Boyd and L. Vandenberghe, Cambridge University Press, 2004. - Selected topics from Ch. 1-5, 9-11 will be covered -- References: CONVEX OPTIMIZATOIN THEORY, by D.P. Bertsekas, Athena Scientific, 2009. NONLINEAR PROGRAMMING, 2ND Ed., by D.P. Bertsekas, Athena Scientific, 1999. The list below is more focused on algorithms AN INTRODUCTION TO OPTIMIZATION, 4th Ed., E.K.P. Chong and S.H. Zak, Wiley, 2013. NUMERICAL OPTIMIZATION, 2nd Ed., by J. Nocedal and S.J. Wright, 2nd Ed., Springer, 2000. -- Lecture notes.

地點

ED 525

時間

15:30 – 18:20, Wed

聯絡方式

Instructor: Office: ED 639, 03-573-1862 Email: c.fung@ieee.org