Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Abstract--We show that the maximization of the sum degreesof-freedom for the static flat-fading multiple-input multipleoutput (MIMO) interference channel is equivalent to a rank co...
Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
As part of the efforts put in understanding the intricacies of the k-colorability problem, different distributions over k-colorable graphs were analyzed. While the problem is notor...
Computing a suitable measure of consensus among several clusterings on the same data is an important problem that arises in several areas such as computational biology and data mi...
Piotr Berman, Bhaskar DasGupta, Ming-Yang Kao, Jie...