Study on Quasi-Linear Support Vector Machine and Its Applications
| Project/Area Number |
25420452
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Control engineering/System engineering
|
|---|
| Research Institution | Waseda University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2013-04-01 – 2017-03-31
|
| Project Status |
Completed (Fiscal Year 2016)
|
| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
|---|
| Keywords | サポートベクターマシン / ニューラルネットワーク / 機械学習 / 適応制御 / パターン認識 / 深層学習 / 局所線形化 / パターン分類 |
|---|
| Outline of Final Research Achievements |
In this research, a quasi-linear support vector machine (SVM) is proposed. The quasi-linear SVM, on one hand, can be seen as a nonlinear SVR model with easy-to-use structure; on the other hand, it is a nonlinear SVM with data-dependent kernel, which can composed by using machine learning methods, kernel learning methods and even deep kernel learning methods. The quasi-linear SVM is applied to switching adaptive control and high-performance pattern recognition.
|
Report
(5 results)
Research Products
(36 results)
