Chinese Journal of Quantum Electronics, Volume. 41, Issue 5, 780(2024)

Ridge regression algorithm based on quantum singular value estimation

CHEN Kangjiong1, GUO Gongde2, and LIN Song2、*
Author Affiliations
  • 1College of Optoelectronics and Information Engineering, Fujian Normal University, Fuzhou 350007, China
  • 2College of Computer and Cyber Security, Fujian Normal University, Fuzhou 350007, China
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    Figures & Tables(7)
    Quantum circuit to obtain ω. Here R is controlled rotation, R=∑θ∈{0,1}dθθ⊗exp (-iθσy). QSVE is singular value estimation operation
    Quantum circuit to get the new predicted value
    Distribution of the results of measuring 01 and 11
    Feasibility simulation experiment quantum circuit diagram of "Estimating the inner product with the measurement probability in the output predicted value"
    Distribution of the results of "the quantum amplitude estimation method is used to obtain the predicted valuein the form of quantum states" measurement
    Feasibility simulation experiment quantum circuit diagram of "using quantum amplitude estimation method to obtain predicted value in quantum state form". Here U is the initial state preparation operator, QFT is the quantum Fourier operator, and Grover is the G-operator in amplitude estimation
    • Table 1. Time complexity comparison between ridge regression algorithms

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      Table 1. Time complexity comparison between ridge regression algorithms

      AlgorithmTime complexity
      Classical ridge regression algorithmΟ(NM+N2Rlog(Rε)/ε2)
      Algorithm in reference [21]OlogM+Ns2κ 3ε-2
      Algorithm in reference [22]OXmax2polylogM+Nκ3ε-3
      The proposed algorithmΟκ2polylogMNε+NpolylogMN+polylogN
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    Kangjiong CHEN, Gongde GUO, Song LIN. Ridge regression algorithm based on quantum singular value estimation[J]. Chinese Journal of Quantum Electronics, 2024, 41(5): 780

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    Paper Information

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    Received: Sep. 21, 2022

    Accepted: --

    Published Online: Jan. 8, 2025

    The Author Email: Song LIN (lins95@fjnu.edu.cn)

    DOI:10.3969/j.issn.1007-5461.2024.05.008

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