A Deep Neural Network Based Quasi-Linear Kernel for Support Vector Machines-Reference-Cited by-同舟云学术

A Deep Neural Network Based Quasi-Linear Kernel for Support Vector Machines

Published:2016 Issue:12 Volume:E99.A Page:2558-2565
ISSN:0916-8508
Container-title:IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
language:en
Short-container-title:IEICE Trans. Fundamentals

Author:

LI Weite¹²,ZHOU Bo¹,CHEN Benhui³,HU Jinglu¹

Affiliation:

1. Graduate School of Information, Production and Systems, Waseda University

2. School of Electrical Engineering, University of Electronic Science and Technology of China

3. School of Mathematics and Computer Science, Dali University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Signal Processing

Link

https://www.jstage.jst.go.jp/article/transfun/E99.A/12/E99.A_2558/_pdf

Reference35 articles.

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3. [3] A. Krizhevsky, I. Sutskever, and G.E. Hinton, “Imagenet classification with deep convolutional neural networks,” Advances in Neural Information Processing Systems, pp.1097-1105, 2012.

4. [4] P.E. Utgoff and D.J. Stracuzzi, “Many-layered learning,” Neural Comput., vol.14, no.10, pp.2497-2529, 2002.

5. [5] G.F. Montufar, R. Pascanu, K. Cho, and Y. Bengio, “On the number of linear regions of deep neural networks,” Advances in Neural Information Processing Systems, pp.2924-2932, 2014.

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