研究課題/領域番号 |
20K11939
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研究機関 | 岩手県立大学 |
研究代表者 |
チャクラボルティ バサビ 岩手県立大学, ソフトウェア情報学部, 教授 (90305293)
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研究期間 (年度) |
2020-04-01 – 2023-03-31
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キーワード | feature selection / metaheuristic algorithm / quantum inspired / optimal feature subset |
研究実績の概要 |
We have developed a new metaheuristic based computationally simple algorithm (Binary owl Serach Algorithm) for optimum feature subset selection. In the next stage, we modified the algorithm by introducing self adaptivity, elitism and mutation operation to strengthen the searching capability of the algorithm for getting better solution. Finally we proposed another extension of the Binary Owl Search algorithm, a quantum inspired binary owl search algorithm, to improve computational time. We have also refined the QUBO formulation of filter function to develop quantum computing based algorithm. We have published two international conference papers and two journal papers. This year we intend to work towards developing a general framework of quantum machine learning.
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現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We could achieve what we planned for the first year of the project. Communication with other members of my team went quite well.
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今後の研究の推進方策 |
Now we are working for evaluation of our proposed algorithms for larger data sets and high dimensional data sets. We are also planning to extend our work for defining a general framework of integration of machine learning with quantum computing.
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次年度使用額が生じた理由 |
Due to pandemic problem, the plan for this year was not fulfilled. The plan for the next year: 1) Buy GPU machine for simulation with high dimensional data. 2)International conference attandance, if possible.
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