Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...
We propose a methodology for improved segmentation of images in a Bayesian framework by fusion of color, texture and gradient information. The proposed algorithm is initialized by...