| Project/Area Number |
20K11939
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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 | Iwate Prefectural University |
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Principal Investigator |
チャクラボルティ バサビ 岩手県立大学, その他部局等, 特命教授 (90305293)
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| Project Period (FY) |
2020-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2022: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2021: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2020: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | Feature subset selection / Quantum based algorithm / Quantum optimization / Quantum machine learning / feature selection / metaheuristic algorithm / quantum inspired / feature subset selection / feature selection / optimal feature subset / quantum machine learning |
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| Outline of Research at the Start |
This research is aimed at developing fast and efficient algorithms for finding out the most important feature subset for recognition, classification and mining of big data in the area of business, medical or social media by novel integration of quantum computing with machine learning.
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| Outline of Annual Research Achievements |
Last year we summarized our research results and drafted a review paper on quantum computing and quantum based metaheuristic algorithms for feature subset selection. This year we examined the draft and revisited our research results from the beginning of the project. We found that our results need to be verified by using real quantum computers instead of only simulation experiments. For this purpose we communicated to research facilities in foreign countries. In May 2023, I visited Regensberg University of Applied Science and the laboratory of Prof. Wolfgang Mauerer, Faculty of Computer Science and Mathematics, OTH-Regensberg.
He works in the area of Quantum Computing and we exchanged ideas of how could we use quantum computing in solving feature selection problem and frame a general approach for quantum machine learning. I used the quantum computing facility of the university to run our proposed algorithms in a small scale environment. Ashis Kumar Mandal, one of the research collaborators of this project is visiting University of Saskatchewan from September 2023. He is engaged in using the university's quantum computing facility. We could run small scale programs in check the plausibility and efficiency of our proposed quantum based algorithms for optimal feature subset selection. We are currently compiling our new results to enhance the draft review paper and will submit to a journal.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Our project progressed smoothly as we planned in the year 2023. We could complete our planned experiments.
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| Strategy for Future Research Activity |
This year we are planning to execute more simulations using quantum computer for data sets containing moderately large number of features. We will compile the results in a paper and submit this paper and the review paper to journal.
I am also planning to attend International conference to communicate our new results.
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