In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
The BaBar experiment at the Stanford Linear Accelerator Center (SLAC) is designed to perform a high precision investigation of the decays of the B-meson produced from electron-pos...
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
Symbolic analysis shows promise as a foundation for bug-finding, specification inference, verification, and test generation. This paper addresses demand-driven symbolic analysi...
We introduce a method that enables scalable image search for learned metrics. Given pairwise similarity and dissimilarity constraints between some images, we learn a Mahalanobis d...