This course treats interior point methods for solving linear programming. Especially, students acquire with mathematical theory, optimal condition, polynomial convergence, and computational efficiency of interior point methods.
In addition, this course teats techniques to mining useful knowledge from Japanese documents. Especially, students study various methods of separating words and word embedding.
By the end of this course, students will be able to:
1. Understand the theoretical properties of interior-point methods for linear programming problems and can apply them to real problems.
2. Understand the theoretical properties of separation words and word embedding for Japanese documents and can apply them to real problems.
Interior-point method, Linear programming, Text mining
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
Attendance is taken in every class.
Students are required to read the text before coming to class.
|Course schedule||Required learning|
|Class 1||Linear programming||We instruct in each class|
|Class 2||Primal interior-point method (affine scaling algorithm)|
|Class 3||Primal interior-point method (Karmarkar's algorithm)|
|Class 4||Analytic center and center path|
|Class 5||Primal-dual interior-point method (affine scaling algorithm)|
|Class 6||Primal-dual interior-point method (path following mathed)|
|Class 7||Infeasible interior-point method|
|Class 8||Japanese documents|
|Class 9||Separating words|
|Class 10||Implementation preparation|
|Class 11||Implementation of Separating words|
|Class 12||Word embedding|
|Class 14||Implementation of Word2Vec|
Course materials can be found on OCW-i
Students will be assessed on their understanding of interior point method, and their ability to apply them to solve problems.
Students' course scores are based on reports (50%) and mini exams (50%).