2018-1 Optimization
Time: Wed 9:00am-12:00
Location: Cluster Bd. R509 (학연산클러스터 509호)
Textbook: Numerical Optimization, Nocedal & Wright, Springer, 2006
Grading:
Homework: 30%
Midterm Exam: 30%
Final Exam 30%
Attendance: 10%
June 15: homework submission: due on June 15 by 13:00 @ Cluster Bd R. 620 (학연산클러스터 620호 인공지능연구실)
June 20: Final Exam
Latex template for scribblers: [tex]
Lecture Notes
Review of analysis (pdf, scribbler: 이정현)
Rate of convergence, descent direction (pdf, scribbler: 김영석)
Differentiation, continuity(pdf, scribbler: 손수현)
HW1 [pdf] : due April 4 (no submission, volunteer-based discussion in class. Updated March 28)
Optimality conditions (pdf, scribbler: 권준형)
Convex optimization (pdf, scribbler: 이정현)
HW2 [pdf]: due April 18 (no submission, volunteer-based discussion in class.)
Convex Optimization (pdf, scribbler: 강동연)
Lipschitz continuity, strong convexity
Midterm exam: April 25 (in class)
You can bring one A4 paper, filling up only ONE-SIDE of the paper with the content from the lecture. This is optional
You can bring your own scratch paper
Exam questions will be at the similar level to the homework questions, but may not be the same
Steepest descent & Newton's method (pdf, scribbler: M. Ibtesam)
Convergence Rate of GD & Newton's method, Quasi-Newton Method (pdf, scribbler: 손수현)
Quasi-Newton Method, Conjugate Gradient Method (pdf, scribbler: Z. Wu)
HW3 [pdf]: due May 30
May 23: Conjugate gradient (pdf, scribbler: 이기찬), SGD (link)
June 5 (make-up lecture): 1:30 ~ 4:30 @ Cluster R.506
June 6: no lecture (memorial day)
June 13: no lecture (election day)
June 15: homework submission: due on June 15 by 13:00 @ Cluster Bd R. 620 (학연산클러스터 620호 인공지능연구실)
June 20: Final Exam