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QUANTUM SPEEDUP OF TRAINING RADIAL BASIS FUNCTION NETWORKS
Shao, Changpeng
2019-06-01
Source PublicationQUANTUM INFORMATION & COMPUTATION
ISSN1533-7146
Volume19Issue:7-8Pages:609-625
AbstractRadial basis function (RBF) network is a simple but useful neural network model that contains wide applications in machine learning. The training of an RBF network reduces to solve a linear system, which is time consuming classically. Based on HHL algorithm, we propose two quantum algorithms to train RBF networks. To apply the HHL algorithm, we choose using the Hamiltonian simulation algorithm proposed in [P. Rebentrost, A. Steffens, I. Marvian and S. Lloyd, Phys. Rev. A 97, 012327, 2018]. However, to use this result, an oracle to query the entries of the matrix of the network should be constructed. We apply the amplitude estimation technique to build this oracle. The final results indicate that if the centers of the RBF network are the training samples, then the quantum computer achieves exponential speedup at the number and the dimension of training samples over the classical computer; if the centers are determined by the K-means algorithm, then the quantum computer achieves quadratic speedup at the number of samples and exponential speedup at the dimension of samples.
Keywordquantum algorithm quantum machine learning radial basis function network
Language英语
Funding ProjectNational Natural Science Foundation of China[11671388] ; CAS Project[QYZDJ-SSW-SYS022]
WOS Research AreaComputer Science ; Physics
WOS SubjectComputer Science, Theory & Methods ; Quantum Science & Technology ; Physics, Particles & Fields ; Physics, Mathematical
WOS IDWOS:000471830800006
PublisherRINTON PRESS, INC
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/35021
Collection中国科学院数学与系统科学研究院
Corresponding AuthorShao, Changpeng
AffiliationChinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Shao, Changpeng. QUANTUM SPEEDUP OF TRAINING RADIAL BASIS FUNCTION NETWORKS[J]. QUANTUM INFORMATION & COMPUTATION,2019,19(7-8):609-625.
APA Shao, Changpeng.(2019).QUANTUM SPEEDUP OF TRAINING RADIAL BASIS FUNCTION NETWORKS.QUANTUM INFORMATION & COMPUTATION,19(7-8),609-625.
MLA Shao, Changpeng."QUANTUM SPEEDUP OF TRAINING RADIAL BASIS FUNCTION NETWORKS".QUANTUM INFORMATION & COMPUTATION 19.7-8(2019):609-625.
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