DeepLTSC: Long-Tail Service Classification via Integrating Category Attentive Deep Neural Network and Feature Augmentation-Reference-Cited by-同舟云学术

DeepLTSC: Long-Tail Service Classification via Integrating Category Attentive Deep Neural Network and Feature Augmentation

Author:

Zou Guobing¹^ORCID,Yang Song¹,Duan Shengyu¹,Zhang Bofeng¹^ORCID,Gan Yanglan²^ORCID,Chen Yixin³^ORCID

Affiliation:

1. School of Computer Engineering and Science, Shanghai University, Shanghai, China

2. School of Computer Science and Technology, Donghua University, Shanghai, China

3. Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA

Funder

National Natural Science Foundation of China

Shanghai Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

Reference36 articles.

1. Empirical evaluation of gated recurrent neural networks on sequence modeling;chung;arXiv 1412 3555,2014

2. Text classification improved by integrating bidirectional LSTM with two-dimensional max pooling;zhou;arXiv 1611 06639,2016

5. Visualizing data using t-SNE;maaten;J Mach Learn Res,2008

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