CO463/663 Winter 2018

Convex Optimization and Analysis

"The great watershed in optimization is not between linearity and nonlinearity, but convexity and nonconvexity." (Rockafellar, 1993.)

Instructor Henry Wolkowicz (MC6065, x35589)

The course is self-contained but uses basic linear algebra (vector spaces/inner-products/basic matrix factorizations/eigen-decompositions) and basic calculus (Taylor series/Implicit function Theorem/continuity/convergence).

Handouts
Syllabus Course/Marking
Links/Announcements
Sample problems/solutions MIT Convex Anal.
Fundamentals of Lin. Alg. and Opt., ebook
A new algorithm that minimizes anything/everything
200 Best Jobs 2014

Time:T-R 2:30-4:00PM; from Thurs. Jan. 4 to Tues. Apr. 3.
Location: DWE 3519
Instructor Office Hour: 2-3 Wed. in MC6312 (or after class Tues/Thurs)
TA: Stefan Sremac, Office Hour: MC 6011, Wed. 1PM.
FINAL EXAM: Monday April 9, 2018, 7:30-10:00PM, location MC 4064

Text:

J.-B. Hiriart-Urruty and C. Lemaréchal, Fundamentals of Convex Analysis, Springer, 2001

(available at reserve desk; 3 hour reserve)

Further References

Latest Course Notes are updated after the lectures and are available at the LEARN webpage.

(Note that these notes are changing during the semester.)

Marking Scheme: HW 50%; Final 50%; Final exam on ?????? ??????, 2018, at ??????location TBA).

HOMEWORK
Expect 6 assignments - to be submitted at the beginning of the class stated on the assignment.