• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Development of Integrated Quantum Inspired Algorithms for Shapley Value based Fast and Interpretable Feature Subset Selection

Research Project

Project/Area Number 24K15089
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 61030:Intelligent informatics-related
Research InstitutionIwate Prefectural University

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)

Co-Investigator(Kenkyū-buntansha) 白田 由香利  学習院大学, 経済学部, 教授 (30337901)
Project Period (FY) 2024-04-01 – 2027-03-31
Project Status Granted (Fiscal Year 2024)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2026: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2025: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2024: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
KeywordsQuantum Machine Learning
Outline of Research at the Start

In the analysis of high dimensional medical, healthcare or finance data, transparency in decision is absolutely important. Selection of the relevant and interpretable features is key to the success of transparent and explainable models. The main objective of this research is to investigate and develop extension of Shapley values (SV) to quantum domain and integrate with our already developed quantum inspired metaheuristic approaches for faster implementation of interpretable optimal feature subset selection algorithms leading to quantum based explainable learning models.

URL: 

Published: 2024-04-05   Modified: 2024-06-24  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi