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...
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...
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...
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,...
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...