We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
This paper compares the ability of human observers to detect target image curves with that of an ideal observer. The target curves are sampled from a generative model which speciļ...
Alan L. Yuille, Fang Fang, Paul R. Schrater, Danie...
āEfļ¬cient server selection algorithms reduce retrieval time for objects replicated on different servers and are an important component of Internet cache architectures. This pap...
Sandra G. Dykes, Kay A. Robbins, Clinton L. Jeffer...
We present a comprehensive treatment of 3D object tracking by posing it as a nonlinear state estimation problem. The measurements are derived using the outputs of shape-encoded fi...
A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, speciļ¬cally the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...