Chinese Journal of Quantum Electronics ›› 2024, Vol. 41 ›› Issue (5): 780-792.doi: 10.3969/j.issn.1007-5461.2024.05.008

• Quantum Optics • Previous Articles     Next Articles

Ridge regression algorithm based on quantum singular value estimation

CHEN Kangjiong1 , GUO Gongde2 , LIN Song2*   

  1. (1 College of Optoelectronics and Information Engineering, Fujian Normal University, Fuzhou 350007, China; 2 College of Computer and Cyber Security, Fujian Normal University, Fuzhou 350007, China)
  • Received:2022-09-21 Revised:2022-10-22 Published:2024-09-28 Online:2024-09-28

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.

Key words: quantum computing, quantum ridge regression, quantum singular value estimation, quantum amplitude estimation

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