Quantum Machine Learning: What Quantum Computing Means to Data Mining
作者： Peter Wittek
DOI:
关键词:
摘要: Quantum Machine Learning bridges the gap between abstract developments in quantum computing and applied research on machine learning. Paring down complexity of disciplines involved, it ...
amazon.com
openlibrary.org
researchgate.net 参考文章(212)
Peter Bartlett, Marcus Frean, Llew Mason, Jonathan Baxter, Boosting Algorithms as Gradient Descent in Function Space ,(2007)
Hans-Peter Kriegel, Martin Ester, Jörg Sander, Xiaowei Xu, A density-based algorithm for discovering clusters in large spatial Databases with Noise knowledge discovery and data mining. pp. 226- 231 ,(1996)
Jerome H. Friedman, Greedy function approximation: A gradient boosting machine. Annals of Statistics. ,vol. 29, pp. 1189- 1232 ,(2001) , 10.1214/AOS/1013203451
Pekka Orponen, Computational complexity of neural networks: a survey Nordic Journal of Computing. ,vol. 1, pp. 94- 110 ,(1994)
Guillaume Stempfel, Liva Ralaivola, Learning SVMs from Sloppily Labeled Data international conference on artificial neural networks. pp. 884- 893 ,(2009) , 10.1007/978-3-642-04274-4_91
A. P. Young, S. Knysh, V. N. Smelyanskiy, First-order phase transition in the quantum adiabatic algorithm. Physical Review Letters. ,vol. 104, pp. 020502- ,(2010) , 10.1103/PHYSREVLETT.104.020502
V. Onclinx, V. Wertz, M. Verleysen, Nonlinear data projection on non-Euclidean manifolds with controlled trade-off between trustworthiness and continuity Neurocomputing. ,vol. 72, pp. 1444- 1454 ,(2009) , 10.1016/J.NEUCOM.2008.12.018
Hwanjo Yu, Jiong Yang, Jiawei Han, Classifying large data sets using SVMs with hierarchical clusters knowledge discovery and data mining. pp. 306- 315 ,(2003) , 10.1145/956750.956786
Lu-Ming Duan, Guang-Can Guo, Probabilistic Cloning and Identification of Linearly Independent Quantum States Physical Review Letters. ,vol. 80, pp. 4999- 5002 ,(1998) , 10.1103/PHYSREVLETT.80.4999
Rigui Zhou, Qiulin Ding, Quantum Pattern Recognition with Probability of 100 International Journal of Theoretical Physics. ,vol. 47, pp. 1278- 1285 ,(2008) , 10.1007/S10773-007-9561-5