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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 Artificial Intelligence
- Instructor(s)
- Suzumura Toyotaro Machida Motoya Alexander Shibakov
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Intensive ()
- Group
- -
- Course number
- ART.T454
- Credits
- 2
- Academic year
- 2018
- Offered quarter
- 1-2Q
- Syllabus updated
- 2018/7/27
- Lecture notes updated
- 2018/6/29
- Language used
- English
- Access Index
-
Lecture
Lecture 1 Various distributions and related stochastic models. (Prof. Machida)
2018.6.27(Wed.) 5-6Session
Lecture
Lecture 2 Introduction to large-scale graph analytics (Prof. Suzumura)
2018.7.2(Mon.) 3-4Session
Lecture
Lecture 3 Large-scale graph database (Prof. Suzumura)
2018.7.2(Mon.) 5-6Session
Lecture
Lecture 4 Large-scale graph analytics and high-performance computing (Prof. Suzumura)
2018.7.3(Tue.) 3-4Session
Lecture
Lecture 5 Integration of large-scale graph analytics and machine learning (Prof. Suzumura)
2018.7.4(Wed.) 5-6Session
Lecture
Lecture 6 Applications of graph-based machine learning (Prof. Suzumura)
2018.7.4(Wed.) 7-8Session
Lecture
Lecture 7 Deep learning-based graph embedding method (Prof. Suzumura)
2018.7.6(Fri.) 3-4Session
Lecture
Lecture 8 Knowledge graph and its application to articial intelligence (Prof. Suzumura)
2018.7.6(Fri.) 5-6Session
Lecture
Lecture 9 Introduction to knowledge graph (Prof. Suzumura)
2018.7.6(Fri.) 7-8Session
Lecture
Lecture 10 Poisson processes and their properties. (Prof. Machida)
2018.7.11(Wed.) 3-4Session
Lecture
Lecture 11 Filtration and martingale in stochastic processes. (Prof. Machida)
2018.7.11(Wed.) 5-6Session
Lecture
Lecture 12 Counting processes, hazard functions, and martingale transform. (Prof. Machida)
2018.7.18(Wed.) 3-4Session
Lecture
Lecture 13 Random censorship model, survival function, and Kaplan-Meier estimator. (Prof. Machida)
2018.7.18(Wed.) 5-6Session
Lecture
Lecture 14 Expectation, variance, and asymptotic properties of martingale transform. (Prof. Machida)
2018.7.25(Wed.) 3-4Session
Lecture
Lecture 15 Comparison of two groups in survival analysis: Linear rank statistics. (Prof. Machida)
2018.7.25(Wed.) 5-6Session
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