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BDA
2007
13 years 9 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
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...
HPDC
2000
IEEE
14 years 1 days ago
Creating Large Scale Database Servers
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...
Jacek Becla, Andrew Hanushevsky
SIGIR
2011
ACM
12 years 10 months ago
Pseudo test collections for learning web search ranking functions
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...
PLDI
2009
ACM
14 years 2 months ago
Snugglebug: a powerful approach to weakest preconditions
Symbolic analysis shows promise as a foundation for bug-finding, specification inference, verification, and test generation. This paper addresses demand-driven symbolic analysi...
Satish Chandra, Stephen J. Fink, Manu Sridharan
CVPR
2008
IEEE
14 years 9 months ago
Fast image search for learned metrics
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...
Prateek Jain, Brian Kulis, Kristen Grauman