2023 Faculty Courses School of Computing Department of Mathematical and Computing Science Graduate major in Mathematical and Computing Science
Statistical Learning Theory
- Academic unit or major
- Graduate major in Mathematical and Computing Science
- Instructor(s)
- Sumio Watanabe
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Tue (M-B107(H104)) / 3-4 Fri (M-B107(H104))
- Class
- -
- Course Code
- MCS.T403
- Number of credits
- 200
- Course offered
- 2023
- Offered quarter
- 2Q
- Syllabus updated
- Jul 8, 2025
- Language
- English
Syllabus
Course overview and goals
This lecture will introduce statistical learning theory. The lectures for 2023 ended in the second quarter.
Course description and aims
Learn, understand, and apply statistical learning theory to the real world.
Keywords
Empirical Process Theory, VC dimension, Kernel method, SVM, boosting
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
To be announced.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | under planning | under planning |
| Class 2 | under planning | under planning |
| Class 3 | under planning | under planning |
| Class 4 | under planning | under planning |
| Class 5 | under planning | under planning |
| Class 6 | under planning | under planning |
| Class 7 | under planning | under planning |
| Class 8 | under planning | under planning |
| Class 9 | under planning | under planning |
| Class 10 | under planning | under planning |
| Class 11 | under planning | under planning |
| Class 12 | under planning | under planning |
| Class 13 | under planning | under planning |
| Class 14 | under planning | under planning |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
Textbook(s)
Takafumi Kanamori, Statistical Learning Theory, Kodansha, 2015
Reference books, course materials, etc.
None
Evaluation methods and criteria
under planning
Related courses
- MCS.T507 ： Theory of Statistical Mathematics
- ART.T458 ： Machine Learning
Prerequisites
None.