The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...
Abstract—This paper revisits the classical problem of multiquery optimization in the context of RDF/SPARQL. We show that the techniques developed for relational and semi-structur...
Wangchao Le, Anastasios Kementsietsidis, Songyun D...
This work presents generalized low-rank signal decompositions with the aid of switching techniques and adaptive algorithms, which do not require eigen-decompositions, for space-ti...
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
In order to perform adequately in real-world situations, a planning system must be able to nd the \best" solution while still supporting anytime behavior. We have developed ...