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- School of Science
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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
- Media-enhanced courses
- Day/Period(Room No.)
- Mon3-4(S422) Thr3-4(S422)
- Group
- -
- Course number
- MCS.T402
- Credits
- 2
- Academic year
- 2019
- Offered quarter
- 3Q
- Syllabus updated
- 2019/3/18
- Lecture notes updated
- 2019/11/25
- Language used
- English
- Access Index
-
Lecture
Lecture 1 Convex sets and related results
2019.9.26(Thu.) 3-4Session
mota19-1(222KB)
Lecture
Lecture 2 Lipschitz continuous differentiable functions
2019.9.30(Mon.) 3-4Session
Lecture
Lecture 3 Minimization algorithms for unconstrained optimization problems
2019.10.3(Thu.) 3-4Session
Lecture
Lecture 4 Optimal conditions for differentiable functions
2019.10.7(Mon.) 3-4Session
Lecture
Lecture 5 Steepest descent method
2019.10.17(Thu.) 3-4Session
Lecture
Lecture 6 The Newton method and conjugate gradient methods
2019.10.21(Mon.) 3-4Session
Lecture
Lecture 7 Quasi-Newton methods
2019.10.24(Thu.) 3-4Session
Lecture
Lecture 8 General assignment to check the comprehension
2019.10.28(Mon.) 3-4Session
Lecture
Lecture 9 Convex functions
2019.10.31(Thu.) 3-4Session
Lecture
Lecture 10 Differentiable Convex functions with Lipschitz continuous gradients
Lecture
Lecture 11 Worse case analysis for gradient based methods
2019.11.7(Thu.) 3-4Session
Lecture
Lecture 12 Steepest descent method for differentiable convex functions
2019.11.11(Mon.) 3-4Session
Lecture
Lecture 13 Estimate sequence in accelerated gradient methods for differentiable convex functions
2019.11.14(Thu.) 3-4Session
Lecture
Lecture 14 Optimality of the accelerated gradient method
Lecture
Lecture 15 Accelerated gradient methods for min-max problems
2019.11.25(Mon.) 3-4Session
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