This work concerns with linear and spatially-adaptive direct reconstruction algorithms for 2-D parallel-beam transmission tomography, extending the Filtered Back-Projection (FBP)....
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Background: Current protein clustering methods rely on either sequence or functional similarities between proteins, thereby limiting inferences to one of these areas. Results: Her...
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...