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» On computational limitations of neural network architectures
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IPPS
2010
IEEE
13 years 5 months 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 ...
PREMI
2005
Springer
14 years 29 days ago
Artificial Neural Network Engine: Parallel and Parameterized Architecture Implemented in FPGA
In this paper we present and analyze an artificial neural network hardware engine, its architecture and implementation. The engine was designed to solve performance problems of the...
Milene Barbosa Carvalho, Alexandre Marques Amaral,...
SOFSEM
2004
Springer
14 years 25 days ago
Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
Matej Makula, Michal Cernanský, Lubica Benu...
EVOW
2008
Springer
13 years 9 months ago
Architecture Performance Prediction Using Evolutionary Artificial Neural Networks
The design of computer architectures requires the setting of multiple parameters on which the final performance depends. The number of possible combinations make an extremely huge ...
Pedro A. Castillo, Antonio Miguel Mora, Juan Juli&...
ACL
2007
13 years 9 months ago
Fast Semantic Extraction Using a Novel Neural Network Architecture
We describe a novel neural network architecture for the problem of semantic role labeling. Many current solutions are complicated, consist of several stages and handbuilt features...
Ronan Collobert, Jason Weston