A Novel Learning Method Based on Combinatorial Feature of Data
Project/Area Number |
20800045
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Research Category |
Grant-in-Aid for Young Scientists (Start-up)
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Allocation Type | Single-year Grants |
Research Field |
Fundamental theory of informatics
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Research Institution | Ishinomaki Senshu University |
Principal Investigator |
HARAGUCHI Kazuya Ishinomaki Senshu University, 理工学部, 助教 (80453356)
|
Research Collaborator |
NAGAMOCHI Hiroshi 京都大学, 大学院・情報学研究科, 教授 (70202231)
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Project Period (FY) |
2008 – 2009
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Project Status |
Completed (Fiscal Year 2009)
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Budget Amount *help |
¥3,042,000 (Direct Cost: ¥2,340,000、Indirect Cost: ¥702,000)
Fiscal Year 2009: ¥1,482,000 (Direct Cost: ¥1,140,000、Indirect Cost: ¥342,000)
Fiscal Year 2008: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
|
Keywords | アルゴリズム / 機械学習 / 情報可視化 / 人工知能 |
Research Abstract |
In this project, we have aimed at establishing a novel learning method based on combinatorial feature of data. For classification, an essential learning problem, we proposed a learning algorithm based on bipartite graph structure. In computational experiments, we observed that its learning ability is competitive with previous methods and is even superior in some special cases.
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Report
(3 results)
Research Products
(13 results)
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[Presentation] Classification by Ordering Data Samples2008
Author(s)
Kazuya Haraguchi, Seok-Hee Hone, Hiroshi Nagamochi
Organizer
Kyoto RIMS Workshop on Acceleration and Visualization of Computation for Enumeration Problems
Place of Presentation
京都大学数理解析研究所
Year and Date
2008-09-29
Related Report
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