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» Listwise approach to learning to rank: theory and algorithm
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ECCV
2008
Springer
14 years 11 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
WWW
2007
ACM
14 years 9 months ago
Generative models for name disambiguation
Name ambiguity is a special case of identity uncertainty where one person can be referenced by multiple name variations in different situations or even share the same name with ot...
Yang Song, Jian Huang 0002, Isaac G. Councill, Jia...
SIGIR
2009
ACM
14 years 3 months ago
An improved markov random field model for supporting verbose queries
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
Matthew Lease
SIGIR
2003
ACM
14 years 2 months ago
Evaluating different methods of estimating retrieval quality for resource selection
In a federated digital library system, it is too expensive to query every accessible library. Resource selection is the task to decide to which libraries a query should be routed....
Henrik Nottelmann, Norbert Fuhr
CIKM
2005
Springer
14 years 2 months ago
Concept-based interactive query expansion
Despite the recent advances in search quality, the fast increase in the size of the Web collection has introduced new challenges for Web ranking algorithms. In fact, there are sti...
Bruno M. Fonseca, Paulo Braz Golgher, Bruno P&ocir...