Ranking queries are essential tools to process large amounts of probabilistic data that encode exponentially many possible deterministic instances. In many applications where unce...
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
This tutorial presents the definition, the models and the techniques of location privacy from the data privacy perspective. By reviewing and revising the state of art research in ...