We present context-sensitive Multiple Task Learning, or csMTL as a method of inductive transfer. It uses additional contextual inputs along with other input features when learning ...
Parallel processors offer a very attractive mechanism for the implementation of large neural networks. Problems in the usage of parallel processing in neural computing involve the...
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
Abstract. This paper introduces the notion of the variadic neural network (VNN). The inputs to a variadic network are an arbitrary-length list of n-tuples of real numbers, where n ...