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» Learning to Select a Ranking Function
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SIGIR
2008
ACM
13 years 7 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
CIKM
2009
Springer
13 years 11 months ago
Efficient feature weighting methods for ranking
Feature weighting or selection is a crucial process to identify an important subset of features from a data set. Removing irrelevant or redundant features can improve the generali...
Hwanjo Yu, Jinoh Oh, Wook-Shin Han
ESANN
2004
13 years 9 months ago
An informational energy LVQ approach for feature ranking
Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a ...
Razvan Andonie, Angel Cataron
COLT
2005
Springer
14 years 1 months ago
Stability and Generalization of Bipartite Ranking Algorithms
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
Shivani Agarwal, Partha Niyogi
ECML
2007
Springer
14 years 2 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales