Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
We present a new, single-rate method for compressing the connectivity information of a connected 2-manifold triangle mesh with or without boundary. Traditional compression schemes...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
As computer applications become larger with every new version, there is a growing need to provide some way for users to manage the interface complexity. There are three different ...
A workshop on Network Analysis and Visualisation was held on September 11, 2005 in Limerick Ireland, in conjunction with 2005 Graph Drawing conference. This report review the backg...