We consider a formal model of stimulus encoding with a circuit consisting of a bank of filters and an ensemble of integrate-and-fire neurons. Such models arise in olfactory system...
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
In signal restoration by Bayesian inference, one typically uses a parametric model of the prior distribution of the signal. Here, we consider how the parameters of a prior model s...
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
We describe a fast Sequential Minimal Optimization (SMO) procedure for solving the dual optimization problem of the recently proposed Potential Support Vector Machine (P-SVM). The...