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» Learning to Select a Ranking Function
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ICML
2004
IEEE
14 years 1 months ago
Optimising area under the ROC curve using gradient descent
This paper introduces RankOpt, a linear binary classifier which optimises the area under the ROC curve (the AUC). Unlike standard binary classifiers, RankOpt adopts the AUC stat...
Alan Herschtal, Bhavani Raskutti
ICIP
2005
IEEE
14 years 9 months ago
Feature selection with nonparametric statistics
In this paper we discuss a general framework for feature selection based on nonparametric statistics. The three stage approach we propose is based on the assumption that the avail...
Emanuele Franceschi, Francesca Odone, Fabrizio Sme...
ICDE
2010
IEEE
171views Database» more  ICDE 2010»
14 years 7 months ago
Surrogate Ranking for Very Expensive Similarity Queries
1 We consider the problem of similarity search in applications where the cost of computing the similarity between two records is very expensive, and the similarity measure is not a...
Chris Jermaine, Fei Xu, Mingxi Wu, Ravi Jampani, T...
CORR
2010
Springer
140views Education» more  CORR 2010»
13 years 8 months ago
Image Segmentation by Discounted Cumulative Ranking on Maximal Cliques
We propose a mid-level image segmentation framework that combines multiple figure-ground hypothesis (FG) constrained at different locations and scales, into interpretations that t...
João Carreira, Adrian Ion, Cristian Sminchi...
JIPS
2007
134views more  JIPS 2007»
13 years 7 months ago
An Efficient Functional Analysis Method for Micro-array Data Using Gene Ontology
: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...