An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
Consider the problem of signal detection via multiple distributed noisy sensors. We propose a linear decision fusion rule to combine the local statistics from individual sensors i...
In this paper we introduce two new methods for solving binary quadratic problems. While spectral relaxation methods have been the workhorse subroutine for a wide variety of comput...
Vision algorithms utilizing camera networks with a common field of view are becoming increasingly feasible and important. Calibration of such camera networks is a challenging and ...
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...