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1504.00941
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A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
3 April 2015
Quoc V. Le
Navdeep Jaitly
Geoffrey E. Hinton
ODL
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Papers citing
"A Simple Way to Initialize Recurrent Networks of Rectified Linear Units"
50 / 353 papers shown
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Noisy Recurrent Neural Networks
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Shehroz S. Khan
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248
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Short-Term Memory Optimization in Recurrent Neural Networks by Autoencoder-based Initialization
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Christopher Ré
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160
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169
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Learning Various Length Dependence by Dual Recurrent Neural Networks
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Shuai Li
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123
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Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks
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293
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Flexible Transmitter Network
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111
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25 Mar 2020
Depth Enables Long-Term Memory for Recurrent Neural Networks
A. Ziv
92
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0
23 Mar 2020
Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted
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1
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1
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1
Minimization: Architecture Design and Generalization Analysis
Huynh Van Luong
Boris Joukovsky
Nikos Deligiannis
166
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0
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Refined Gate: A Simple and Effective Gating Mechanism for Recurrent Units
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Yunlu Xu
Mingjian Cheng
Yu Qiao
Shiliang Pu
Yi Niu
Leilei Gan
111
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0
26 Feb 2020
Evaluating complexity and resilience trade-offs in emerging memory inference machines
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T. Xiao
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S. Agarwal
S. Cardwell
M. Marinella
William M. Severa
Brad Aimone
114
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Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent
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T. Nguyen
Andrea L. Bertozzi
Richard G. Baraniuk
Stanley J. Osher
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182
54
0
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A Spike in Performance: Training Hybrid-Spiking Neural Networks with Quantized Activation Functions
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Daniel Rasmussen
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190
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Encoding-based Memory Modules for Recurrent Neural Networks
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A. Sperduti
D. Bacciu
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109
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Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks
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Wei Hu
Lechao Xiao
Jeffrey Pennington
198
128
0
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