This paper presents a new adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated a...
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
We consider the problem of tactile discrimination, with the goal of estimating an underlying state parameter in a sequential setting. If the data is continuous and highdimensional...
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....
Recently, we have introduced a novel approach to dynamic programming and reinforcement learning that is based on maintaining explicit representations of stationary distributions i...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...