While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the componen...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
Sets of multi-view images that capture plenoptic information from different viewpoints are typically related by geometric constraints. The proper analysis of these constraints is ...
We introduce Indented Pixel Tree Plots (IPTPs): a novel pixel-based visualization technique for depicting large hierarchies. It is inspired by the visual metaphor of indented outli...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...