In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
In disclosing micro-data with sensitive attributes, the goal is usually two fold. First, the data utility of disclosed data should be maximized for analysis purposes. Second, the ...
We investigate to what extent flooding and routing is possible if the graph is allowed to change unpredictably at each time step. We study what minimal requirements are necessary...
Most algorithms for reconstructing shape from defocus assume that the images are obtained with a camera that has been previously calibrated so that the aperture, focal plane, and ...
Yifei Lou, Paolo Favaro, Andrea L. Bertozzi, Stefa...
This paper introduces a foundation for inductive learning based on the use of higher-order logic for knowledge representation. In particular, the paper (i) provides a systematic i...
Antony F. Bowers, Christophe G. Giraud-Carrier, Jo...