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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Mathematical and Computing Science
- Instructor(s)
- Fukuda Mituhiro Yamashita Makoto
- Class Format
- Lecture (ZOOM)
- Media-enhanced courses
- Day/Period(Room No.)
- Mon3-4(W834) Thr3-4(W834)
- Group
- -
- Course number
- MCS.T402
- Credits
- 2
- Academic year
- 2020
- Offered quarter
- 2Q
- Syllabus updated
- 2020/9/18
- Lecture notes updated
- 2020/8/8
- Language used
- English
- Access Index
-
Lecture
Lecture 1 Convex sets and related results
mota0625-1.10(594KB)
Lecture
Lecture 2 Lipschitz continuous differentiable functions
2020.6.25(Thu.) 3-4Session
Lecture
Lecture 3 Minimization algorithms for unconstrained optimization problems
2020.6.29(Mon.) 3-4Session
Lecture
Lecture 4 Optimal conditions for differentiable functions
2020.7.2(Thu.) 3-4Session
Lecture
Lecture 5 Steepest descent method
2020.7.6(Mon.) 3-4Session
Lecture
Lecture 6 The Newton method and conjugate gradient methods
2020.7.9(Thu.) 3-4Session
Lecture
Lecture 7 Quasi-Newton methods
2020.7.13(Mon.) 3-4Session
Lecture
Lecture 8 Convex functions
2020.7.16(Thu.) 3-4Session
Lecture
Lecture 9 Differentiable convex functions with Lipschitz continuous gradients
Lecture
Lecture 10 Worse case analysis for gradient based methods
2020.7.23(Thu.) 3-4Session
Lecture
Lecture 11 Steepest descent method for differentiable convex functions
2020.7.27(Mon.) 3-4Session
Lecture
Lecture 12 Estimate sequence in accelerated gradient methods for differentiable convex functions
2020.7.30(Thu.) 3-4Session
Lecture
Lecture 13 Optimality of the accelerated gradient method
2020.8.3(Mon.) 3-4Session
Lecture
Lecture 14 Accelerated gradient methods for min-max problems
2020.8.6(Thu.) 3-4Session
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