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ICANN
2001
Springer
14 years 2 days ago
On-Line Learning Methods for Gaussian Processes
Shigeyuki Oba, Masa-aki Sato, Shin Ishii
ICONIP
2007
13 years 9 months ago
Practical Recurrent Learning (PRL) in the Discrete Time Domain
One of the authors has proposed a simple learning algorithm for recurrent neural networks, which requires computational cost and memory capacity in practical order O(n2 )[1]. The a...
Mohamad Faizal Bin Samsudin, Takeshi Hirose, Katsu...
NN
1998
Springer
108views Neural Networks» more  NN 1998»
13 years 7 months ago
How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Tsungnan Lin, Bill G. Horne, C. Lee Giles
ITNG
2010
IEEE
13 years 6 months ago
Scalable Intrusion Detection with Recurrent Neural Networks
The ever-growing use of the Internet comes with a surging escalation of communication and data access. Most existing intrusion detection systems have assumed the one-size-fits-all...
Longy O. Anyanwu, Jared Keengwe, Gladys A. Arome
AGI
2011
12 years 11 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia