2022 Fiscal Year Final Research Report
Machine Learning on Large Graphs
| Project/Area Number |
18K11434
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 61030:Intelligent informatics-related
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Keywords | machine learning / Graph analysis / bioinformatics |
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| Outline of Final Research Achievements |
We have achieved some theoretical and application results on this project. For theoretical, we laid a foundation for learning on hypergraphs, an extension of graphs. We also could apply learning on graphs to complicated applications involving molecules and its interactions with others by leveraging graph information.
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| Free Research Field |
machine learning
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| Academic Significance and Societal Importance of the Research Achievements |
Our achievements help pay ways for further research into more complicated problems in the area of graphs, hypergraphs and application on molecular learning. This may contribute to further research and development in biomedical applications.
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