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» On higher-order perceptron algorithms
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JMLR
2012
11 years 11 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
COLT
1997
Springer
14 years 19 days ago
General Convergence Results for Linear Discriminant Updates
The problem of learning linear discriminant concepts can be solved by various mistake-driven update procedures, including the Winnow family of algorithms and the well-known Percep...
Adam J. Grove, Nick Littlestone, Dale Schuurmans
ICML
2005
IEEE
14 years 9 months ago
Online learning over graphs
We apply classic online learning techniques similar to the perceptron algorithm to the problem of learning a function defined on a graph. The benefit of our approach includes simp...
Mark Herbster, Massimiliano Pontil, Lisa Wainer
ICASSP
2009
IEEE
14 years 3 months ago
A split quaternion nonlinear adaptive filter
A split quaternion learning algorithm for the training of nonlinear finite impulse response filters for the modelling of hypercomplex signals is proposed. A rigorous derivation ...
Bukhari Che Ujang, Clive Cheong Took, Alek Kavcic,...
PROCEDIA
2010
105views more  PROCEDIA 2010»
13 years 6 months ago
Improvement of parallelization efficiency of batch pattern BP training algorithm using Open MPI
The use of tuned collective’s module of Open MPI to improve a parallelization efficiency of parallel batch pattern back propagation training algorithm of a multilayer perceptron...
Volodymyr Turchenko, Lucio Grandinetti, George Bos...