The paper presents a new data partitioning algorithm for parallel computing on heterogeneous processors. Like traditional functional partitioning algorithms, the algorithm assumes ...
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...