A Survey of Techniques All Classifiers Can Learn from Deep Networks: Models, Optimizations, and Regularization

10 September 2019

Papers citing "A Survey of Techniques All Classifiers Can Learn from Deep Networks: Models, Optimizations, and Regularization"

4 / 4 papers shown

Title
A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic Data Abien Fred Agarap 35 216 0 10 Sep 2017
Embedding Visual Hierarchy with Deep Networks for Large-Scale Visual Recognition Tianyi Zhao Baopeng Zhang Wei Zhang Ning Zhou Jun-chen Yu Jianping Fan BDL VLM 25 34 0 08 Jul 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016
Gene selection with guided regularized random forest Houtao Deng G. Runger 94 288 0 28 Sep 2012