The human ability to learn difficult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
We present a class of models that, via a simple construction,
enables exact, incremental, non-parametric, polynomial-time,
Bayesian inference of conditional measures. The approac...
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
We present two new hyperbolic source probability models to effectively represent sub-gaussian and super-gaussian families of sources for dynamic and convolutive Blind Source Recov...
Data from several projects show a significant relationship between the size of a module and its defect density. Here we address implications of this observation. Does the overall ...