We develop a family of upper and lower bounds on the worst-case expected KL loss for estimating a discrete distribution on a finite number m of points, given N i.i.d. samples. Our...
Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...
We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our...
In this paper, we propose a new vector quantization method to create video thumbnail. In particular, we employ video time density function (VTDF) to explore the temporal character...