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» Ranking Categorical Features Using Generalization Properties
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ICML
2007
IEEE
14 years 10 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
IPM
2008
100views more  IPM 2008»
13 years 9 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
SIGMOD
2009
ACM
137views Database» more  SIGMOD 2009»
14 years 9 months ago
Robust and efficient algorithms for rank join evaluation
In the rank join problem we are given a relational join R1 1 R2 and a function that assigns numeric scores to the join tuples, and the goal is to return the tuples with the highes...
Jonathan Finger, Neoklis Polyzotis
ICASSP
2009
IEEE
14 years 3 months ago
Generalized mutual interdependence analysis
The mean of a data set is one trivial representation of data from one class. Recently, mutual interdependence analysis (MIA) has been successfully used to extract more involved re...
Heiko Claussen, Justinian Rosca, Robert I. Damper
WWW
2010
ACM
14 years 4 months ago
Sampling high-quality clicks from noisy click data
Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...
Adish Singla, Ryen W. White