2018 Mathematical Optimization: Theory and Algorithms

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Academic unit or major
Graduate major in Mathematical and Computing Science
Instructor(s)
Fukuda Mituhiro  Yamashita Makoto 
Course component(s)
Lecture
Day/Period(Room No.)
Mon3-4(W832)  Thr3-4(W832)  
Group
-
Course number
MCS.T402
Credits
2
Academic year
2018
Offered quarter
3Q
Syllabus updated
2018/3/20
Lecture notes updated
2018/11/21
Language used
English
Access Index

Lecture

Lecture 1 Convex sets and related results

2018.9.27(Thu.) 3-4Session

Lecture

Lecture 2 Lipschitz continuous differentiable functions

2018.10.1(Mon.) 3-4Session

Lecture

Lecture 3 Minimization algorithms for unconstrained optimization problems

2018.10.4(Thu.) 3-4Session

Lecture

Lecture 4 Optimal conditions for differentiable functions

2018.10.11(Thu.) 3-4Session

Lecture

Lecture 5 Steepest descent method

2018.10.15(Mon.) 3-4Session

Lecture

Lecture 6 Newton method, conjugate gradient methods

2018.10.18(Thu.) 3-4Session

Lecture

Lecture 7 Quasi-Newton methods, convex differentiable function

2018.10.22(Mon.) 3-4Session

Lecture

Lecture 8 General assignment to check the comprehension

2018.10.25(Thu.) 3-4Session

Lecture

Lecture 9 Differentiable Convex functions with Lipschitz continuous gradients

2018.10.29(Mon.) 3-4Session

Lecture

Lecture 10 Worse case analysis for gradient based methods

2018.11.1(Thu.) 3-4Session

Lecture

Lecture 11 Steepest descent method for differentiable convex functions

2018.11.5(Mon.) 3-4Session

Lecture

Lecture 12 Estimate sequence in accelerated gradient methods for differentiable convex functions

2018.11.8(Thu.) 3-4Session

Lecture

Lecture 13 Accelerated gradient method for differentiable convex functions

2018.11.12(Mon.) 3-4Session

Lecture

Lecture 14 Optimality of the accelerated gradient method

2018.11.15(Thu.) 3-4Session

Lecture

Lecture 15 Accelerated gradient methods for min-max problems

2018.11.19(Mon.) 3-4Session

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