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103
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BC
2006
105views more  BC 2006»
15 years 2 months ago
A stochastic population approach to the problem of stable recruitment hierarchies in spiking neural networks
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...
Cengiz Günay, Anthony S. Maida
128
Voted
IPPS
2010
IEEE
15 years 19 days ago
Acceleration of spiking neural networks in emerging multi-core and GPU architectures
Recently, there has been strong interest in large-scale simulations of biological spiking neural networks (SNN) to model the human brain mechanisms and capture its inference capabi...
Mohammad A. Bhuiyan, Vivek K. Pallipuram, Melissa ...
127
Voted
NCI
2004
132views Neural Networks» more  NCI 2004»
15 years 4 months ago
A comparison between spiking and differentiable recurrent neural networks on spoken digit recognition
In this paper we demonstrate that Long Short-Term Memory (LSTM) is a differentiable recurrent neural net (RNN) capable of robustly categorizing timewarped speech data. We measure ...
Alex Graves, Nicole Beringer, Jürgen Schmidhu...
109
Voted
IJCNN
2000
IEEE
15 years 7 months ago
Applying CMAC-Based On-Line Learning to Intrusion Detection
The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existin...
James Cannady
115
Voted
IJCAI
2007
15 years 4 months ago
Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD...
Ah-Hwee Tan