This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
Abstract. Moving object environments are characterized by large numbers of objects continuously sending location updates. At times, data arrival rates may spike up, causing the loa...
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...
We present an approximation scheme for optimizing certain Quadratic Integer Programming problems with positive semidefinite objective functions and global linear constraints. Thi...