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IR
2010
13 years 3 months ago
Gradient descent optimization of smoothed information retrieval metrics
Abstract Most ranking algorithms are based on the optimization of some loss functions, such as the pairwise loss. However, these loss functions are often different from the criter...
Olivier Chapelle, Mingrui Wu
NIPS
2008
13 years 6 months ago
ICA based on a Smooth Estimation of the Differential Entropy
In this paper we introduce the MeanNN approach for estimation of main information theoretic measures such as differential entropy, mutual information and divergence. As opposed to...
Lev Faivishevsky, Jacob Goldberger
ICIP
2005
IEEE
14 years 6 months ago
An articulated registration method
This paper introduces a new registration method estimating the displacement field of bodies which deformations are constrained by an articulated rigid body. We propose an articula...
Aloys du Bois d'Aische, Mathieu De Craene, Beno&ic...
ICML
2009
IEEE
14 years 5 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
PR
2006
164views more  PR 2006»
13 years 4 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung