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Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to
  Probe and Learn Neural Networks

Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks

3 February 2015
Shiliang Zhang
Hui Jiang
    3DV
ArXivPDFHTML

Papers citing "Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks"

3 / 3 papers shown
Title
Feedforward Sequential Memory Networks: A New Structure to Learn
  Long-term Dependency
Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency
Shiliang Zhang
Cong Liu
Hui Jiang
Si Wei
Lirong Dai
Yu Hu
26
75
0
28 Dec 2015
A Fixed-Size Encoding Method for Variable-Length Sequences with its
  Application to Neural Network Language Models
A Fixed-Size Encoding Method for Variable-Length Sequences with its Application to Neural Network Language Models
Shiliang Zhang
Hui Jiang
Mingbin Xu
Junfeng Hou
Lirong Dai
22
13
0
06 May 2015
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,638
0
03 Jul 2012
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