IEOR 262B: Mathematical Programming II
Instructor: Javad Lavaei
Time: Tuesdays and Thursdays, 12:30-2pm
Location: 3119 Etcheverry
TA: SangWoo Park (spark111 AT berkeley.edu)
Instructor's Office Hours: Mondays, 11am-noon (4121 Etcheverry)
TA's Office Hours: Wednesdays, 10:00-11:15am (4176-A Etcheverry)
Grading Policy:
15% homework
40% exam
45% project
Description
This course provides a fundamental understanding of general nonlinear optimization theory, convex optimization, conic optimization, numerical algorithms, and distributed computation. Some of the topics covered in this course are as follows:
Local and global optimality
Optimality conditions
Lagrangian and duality
Convex optimization
Conic optimization
Low-rank optimization
Convexification techniques and hierarchies of convex relaxation
Numerical algorithms and convergence analysis (including descent algorithms, interior-point methods, etc. )
Decomposition and distributed algorithms
Textbook
‘‘Low-Rank Semidefinite Programming: Theory and Applications" by Alex Lemon, Anthony Man-Cho So and Yinyu Ye, Foundations and Trends in Optimization, 2015 (click here to download the monograph).
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