In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...
Synaptic runaway denotes the formationof erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synapti...
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Support Vector Machines (SVMs) perform pattern recognition between two point classes by nding a decision surface determined by certain points of the training set, termed Support V...