Learning Rule for a Quantum Neural Network Inspired by Hebbian Learning
Author:
Affiliation:
1. Laboratory for Nanoelectronics and Spintronics, Research Institute of Electrical Communication, Tohoku University
2. Department of Electrical and Electronics Engineering, University of the Ryukyus
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E104.D/2/E104.D_2020EDP7093/_pdf
Reference28 articles.
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3. [3] C.C. McGeoch and C. Wang, “Experimental evaluation of an adiabiatic quantum system for combinatorial optimization,” Proc. ACM International Conference on Computing Frontiers, p.23, ACM, 2013. 10.1145/2482767.2482797
4. [4] P.W. Shor, “Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer,” SIAM Review, vol.41, no.2, pp.303-332, 1999. 10.1137/s0036144598347011
5. [5] L.K. Grover, “A fast quantum mechanical algorithm for database search,” Proc. twenty-eighth annual ACM symposium on Theory of computing, pp.212-219, ACM, 1996. 10.1145/237814.237866
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