Quantum generative adversarial network for generating discrete distribution

H Situ, Z He, Y Wang, L Li, S Zheng - Information Sciences, 2020 - Elsevier
Quantum machine learning has recently attracted much attention from the community of
quantum computing. In this paper, we explore the ability of generative adversarial networks …

[HTML][HTML] A survey on HHL algorithm: From theory to application in quantum machine learning

B Duan, J Yuan, CH Yu, J Huang, CY Hsieh - Physics Letters A, 2020 - Elsevier
Abstract The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum
linear system of equations that may be found at the core of various scientific applications …

Quantum data compression by principal component analysis

CH Yu, F Gao, S Lin, J Wang - Quantum Information Processing, 2019 - Springer
Data compression can be achieved by reducing the dimensionality of high-dimensional but
approximately low-rank datasets, which may in fact be described by the variation of a much …

Quantum machine learning for support vector machine classification

SS Kavitha, N Kaulgud - Evolutionary Intelligence, 2024 - Springer
Quantum machine learning aims to execute machine learning algorithms in quantum
computers by utilizing powerful laws like superposition and entanglement for solving …

Quantum algorithms for anomaly detection using amplitude estimation

M Guo, H Liu, Y Li, W Li, F Gao, S Qin, Q Wen - Physica A: Statistical …, 2022 - Elsevier
Anomaly detection, as an important branch of machine learning, plays a critical role in fraud
detection, health care, intrusion detection, military surveillance, etc. An anomaly detection …

Toward implementing efficient image processing algorithms on quantum computers

F Yan, SE Venegas-Andraca, K Hirota - Soft Computing, 2023 - Springer
Quantum information science is an interdisciplinary subject spanning physics, mathematics,
and computer science. It involves finding new ways to apply natural quantum-mechanical …

Effective implementation of nonadiabatic geometric quantum gates of cat-state qubits using an auxiliary qutrit

YH Kang, Y Xiao, ZC Shi, Y Wang, JQ Yang… - New Journal of …, 2023 - iopscience.iop.org
We propose an effective protocol for the implementation of nonadiabatic geometric quantum
gates of cat-state qubits in Kerr-nonlinear resonators driven by two-photon squeezing drives …

Quantum circuit learning with parameterized boson sampling

J Shi, Y Tang, Y Lu, Y Feng, R Shi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A quantum circuit learning approach is studied to carry out the fast-fitting of Gaussian
functions. First, a parameterized structure is designed for quantum circuits based on the …

Quantum algorithm for unsupervised anomaly detection

M Guo, S Pan, W Li, F Gao, S Qin, XL Yu… - Physica A: Statistical …, 2023 - Elsevier
Anomaly detection, an important branch of machine learning, plays a critical role in fraud
detection, health care, intrusion detection, military surveillance, etc. As one of the most …

Improved quantum algorithm for A-optimal projection

SJ Pan, LC Wan, HL Liu, QL Wang, SJ Qin, QY Wen… - Physical Review A, 2020 - APS
Dimensionality reduction algorithms, which reduce the dimensionality of a given data set
whereas preserving the information of the original data set as well as possible, play an …