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» On learning linear ranking functions for beam search
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IR
2010
13 years 6 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
ICML
2006
IEEE
14 years 8 months ago
Generalized spectral bounds for sparse LDA
We present a discrete spectral framework for the sparse or cardinality-constrained solution of a generalized Rayleigh quotient. This NPhard combinatorial optimization problem is c...
Baback Moghaddam, Yair Weiss, Shai Avidan
SIGIR
2010
ACM
13 years 11 months ago
Learning more powerful test statistics for click-based retrieval evaluation
Interleaving experiments are an attractive methodology for evaluating retrieval functions through implicit feedback. Designed as a blind and unbiased test for eliciting a preferen...
Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, T...
SIGIR
2004
ACM
14 years 1 months ago
A joint framework for collaborative and content filtering
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...
Justin Basilico, Thomas Hofmann
MM
2003
ACM
113views Multimedia» more  MM 2003»
14 years 24 days ago
The combination limit in multimedia retrieval
Combining search results from multimedia sources is crucial for dealing with heterogeneous multimedia data, particularly in multimedia retrieval where a final ranked list of item...
Rong Yan, Alexander G. Hauptmann