While recommender systems tell users what items they might like, explanations of recommendations reveal why they might like them. Explanations provide many benefits, from improvi...
We present a novel reranking framework for Content Based Image Retrieval (CBIR) systems based on con-textual dissimilarity measures. Our work revisit and extend the method of Perro...
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
Abstract. This paper considers the probabilistic may/must testing theory for processes having external, internal, and probabilistic choices. We observe that the underlying testing ...
Abstract—By accurately measuring risk for enterprise networks, attack graphs allow network defenders to understand the most critical threats and select the most effective counter...
Kyle Ingols, Matthew Chu, Richard Lippmann, Seth E...