The paper presents a novel multi-view learning framework based on variational inference. We formulate the framework as a graph representation in form of graph factorization: the g...
This work explores issues of computational disclosure control. We examine assumptions in the foundations of traditional problem statements and abstract models. We offer a comprehe...
Rick Crawford, Matt Bishop, Bhume Bhumiratana, Lis...
: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informativ...
In this paper we present a novel algorithm for video scene segmentation. We model a scene as a semantically consistent chunk of audio-visual data. Central to the segmentation fram...
We consider how to exploit the correlation in image for compression by virtue of studying image patches in a nonparametric manner. Instead of extracting and recording parameters, ...