量子电子学报2024，Vol.41Issue(5)：780-792,13.DOI:10.3969/j.issn.1007-5461.2024.05.008
基于量子奇异值估计的岭回归算法
Ridge regression algorithm based on quantum singular value estimation
摘要
Abstract
As a kind of supervised learning algorithm,ridge regression algorithm has a wide range of applications.A quantum ridge regression algorithm is proposed by combining quantum singular value estimation with classical ridge regression algorithm.In the proposed algorithm,the parallel property of quantum computation is utilized to solve the fitting parameters of ridge regression and obtain the predicted values.Complexity analysis shows that the proposed algorithm effectively solves the problem of matrix expansion or matrix operation when the data matrix is non-Hermitian matrix,and has exponential acceleration in running time compared with the classical algorithms.In addition,the quantum circuit diagram of the proposed algorithm is also provided and the key steps of the algorithm are simulated.The simulation results confirm its effectiveness and feasibility.关键词
量子计算/量子岭回归/量子奇异值估计/量子幅度估计Key words
quantum computing/quantum ridge regression/quantum singular value estimation/quantum amplitude estimation分类
信息技术与安全科学引用本文复制引用
陈康炯,郭躬德,林崧..基于量子奇异值估计的岭回归算法[J].量子电子学报,2024,41(5):780-792,13.基金项目
国家自然科学基金(62171131,61976053,61772134),福建省高等学校新世纪优秀人才支持计划,福建省自然科学基金(2022J01186) （62171131,61976053,61772134）
