3. 강의목표
The primary goal of this course is to provide ideas and analysis for convex optimization problems that arise frequently in many scientific and engineering disciplines. This includes first-order methods for both unconstrained and constrained optimization problems, duality theory and dual-based methods, and possibly some modern methods for large-scale optimization problems.
4. 강의선수/수강필수사항
- Good knowledge in mathematics linear algebra and calculus.
- Basic skills for scientific and numerical computing.
- Exposure to optimization and application fields.
5. 성적평가
- Participation: 10%
- Quizzes: 10%
- Assignments: 20%
- Midterm exam: 30%
- Final exam: 30%
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
No specific textbook is required; lecture notes will be provided instead.
|
|
|
0000
|
|
7. 참고문헌 및 자료
- Convex Optimization, Stephen Boyd and Lieven Vandenberghe
- Convex Optimization: Algorithms and Complexity, Sebastien Bubeck
- Lectures on Convex Optimization, Yurii Nesterov
8. 강의진도계획
Part 1: Fundamentals (Weeks 1-2)
- Introduction
- Mathematical preliminaries
- Convex sets, functions, optimization
Part 2: Unconstrained optimization (Weeks 3-5)
- Gradient methods
- Subgradient methods
- Accelerated gradient methods
Part 3: Constrained optimization (Weeks 6-7)
- Proximal gradient methods
- Mirror descent methods
- Frank-Wolfe method
Midterm exam (Week 8)
Part 4: Duality (Weeks 9-12)
- KKT conditions
- Lagrange Duality
- Dual projected subgradient methods
- Dual proximal gradient methods
- Augmented Lagrangian methods
- Alternating direction method of multipliers
Part 5: Second-order methods (Week 13)
- Newton’s method
- Quasi-Newton methods
Part 6: Large-scale optimization (Weeks 14-15)
- Stochastic gradient methods
- Distributed optimization
- Non-convex optimization
Final exam (Week 16)
9. 수업운영
- This course is a standard lecture-based course where the instructor delivers a series of lectures.
- Students will receive a few assignments to perform throughout the course.
- Students will be evaluated through quizzes and exams.
- There is no group work in this course.
- This course will be delivered live on campus
10. 학습법 소개 및 기타사항
The plan outlined in the syllabus is subject to change due to unforeseen circumstances.
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청