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ICML
2010
IEEE
15 years 7 days ago
Rectified Linear Units Improve Restricted Boltzmann Machines
Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all ...
Vinod Nair, Geoffrey E. Hinton
IPPS
1998
IEEE
15 years 3 months ago
Artificial Neural Networks on Reconfigurable Meshes
:Artificial neural networks(ANN) have been used successfully in applications such as pattern recognition, image processing, automation and control. Majority of today's applica...
Jing-Fu Fu Jenq, Wing Ning Li
ISCAS
1995
IEEE
116views Hardware» more  ISCAS 1995»
15 years 2 months ago
Capabilities and Limitations of Feedforward Neural Networks with Multilevel Neurons
This paper proposes a multilevel logic approach to output coding using multilevel neurons in the output layer. Training convergence for a single multilevel perceptron is considere...
Aleksander Malinowski, Tomasz J. Cholewo, Jacek M....
NECO
2008
146views more  NECO 2008»
14 years 11 months ago
Deep, Narrow Sigmoid Belief Networks Are Universal Approximators
In this paper we show that exponentially deep belief networks [3, 7, 4] can approximate any distribution over binary vectors to arbitrary accuracy, even when the width of each lay...
Ilya Sutskever, Geoffrey E. Hinton
ICASSP
2008
IEEE
15 years 5 months ago
Ratio semi-definite classifiers
We present a novel classification model that is formulated as a ratio of semi-definite polynomials. We derive an efficient learning algorithm for this classifier, and apply it...
Jonathan Malkin, Jeff Bilmes