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» Listwise approach to learning to rank: theory and algorithm
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WINE
2010
Springer
124views Economy» more  WINE 2010»
13 years 6 months ago
A Novel Approach to Propagating Distrust
Trust propagation is a fundamental topic of study in the theory and practice of ranking and recommendation systems on networks. The Page Rank [9] algorithm ranks web pages by propa...
Christian Borgs, Jennifer T. Chayes, Adam Tauman K...
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
13 years 7 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
CIKM
2010
Springer
13 years 7 months ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang
JMLR
2012
11 years 11 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
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...
Alexandre Lacoste, François Laviolette, Mar...
CIKM
2008
Springer
13 years 11 months ago
Ranked feature fusion models for ad hoc retrieval
We introduce the Ranked Feature Fusion framework for information retrieval system design. Typical information retrieval formalisms such as the vector space model, the bestmatch mo...
Jeremy Pickens, Gene Golovchinsky