In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
Abstract-- Many popular Web sites suffer occasional uservisible problems such as slow responses, blank pages or error messages being displayed, items not being added to shopping ca...
In this paper, we present an adaptive load diffusion operator to enable scalable processing of Multiway Windowed Stream Joins (MWSJs) using a cluster system. The load diffusion is...
Efficiently and accurately searching for similarities among time series and discovering interesting patterns is an important and non-trivial problem. In this paper, we introduce a...