A Deep Learning Approach to DNA Sequence Classification-Reference-Cited by-同舟云学术

A Deep Learning Approach to DNA Sequence Classification

Published:2016 Issue: Volume: Page:129-140
ISSN:0302-9743
Container-title:Computational Intelligence Methods for Bioinformatics and Biostatistics
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Author:

Rizzo Riccardo,Fiannaca Antonino,La Rosa Massimo,Urso Alfonso

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-44332-4_10

Reference28 articles.

1. Bengio, Y.: Learning deep architectures for AI. Found. Trends Mach. Learn. 2(1), 1–127 (2009)

2. Coates, A., Ng, A.Y., Lee, H.: An analysis of single-layer networks in unsupervised feature learning. In: International Conference on Artificial Intelligence and Statistics, pp. 215–223 (2011)

3. LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278–2324 (1998)

4. Farabet, C., Couprie, C., Najman, L., LeCun, Y.: Learning hierarchical features for scene labeling. IEEE Trans. Pattern Anal. Mach. Intell. 35(8), 1915–1929 (2013)

5. Sukittanon, S., Surendran, A., Platt, J., Burges, C.: Convolutional Networks for Speech Detection. In: Interspeech, International Speech Communication Association (2004)

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