In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians...
We investigate under what conditions clustering by learning a mixture of spherical Gaussians is (a) computationally tractable; and (b) statistically possible. We show that using p...
Nathan Srebro, Gregory Shakhnarovich, Sam T. Rowei...
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Abstract— Ultra wide band (UWB) impulse radio (IR) technology calls for robust and low-complexity receiver techniques. State-of-the-art proposals are both coherent ML receivers, ...
—We present solutions to two problems that prevent the effective use of population-based algorithms in clustering problems. The first solution presents a new representation for ...