We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
Bruno Apolloni, Andrea Brega, Dario Malchiodi, Gio...
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
We introduce a new learning algorithm for topographic map formation of Edgeworth-expanded Gaussian activation kernels. In order to avoid the rapid increase in kernel parameters, a...
If a wearable device can register what the wearer is currently doing, it can anticipate and adjust its behavior to avoid redundant interaction with the user. However, the relevanc...