Training neural networks on high-dimensional data using random projection-Reference-Cited by-同舟云学术

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Training neural networks on high-dimensional data using random projection

Published:2018-03-19 Issue:3 Volume:22 Page:1221-1231
ISSN:1433-7541
Container-title:Pattern Analysis and Applications
language:en
Short-container-title:Pattern Anal Applic

Author:

Wójcik Piotr Iwo,Kurdziel Marcin

Funder

Polish National Science Centre

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition

Link

http://link.springer.com/content/pdf/10.1007/s10044-018-0697-0.pdf

Reference49 articles.

1. LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436–444

2. Graves A, Mohamed A, Hinton G (2013) Speech recognition with deep recurrent neural networks. In: Proceedings of 2013 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 6645–6649

3. Yuan G-X, Ho C-H, Lin C-J (2012) Recent advances of large-scale linear classification. Proceedings of the IEEE 100(9):2584–2603

4. Johnson WB, Lindenstrauss J (1984) Extensions of Lipschitz mappings into a Hilbert space. Contemp Math 26:189–206

5. Indyk P, Motwani R (1998) Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the 13th annual ACM symposium on theory of computing. ACM, pp 604–613

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