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ICML
2009
IEEE
15 years 10 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
CN
2010
110views more  CN 2010»
14 years 10 months ago
End-to-end quality of service seen by applications: A statistical learning approach
The focus of this work is on the estimation of quality of service (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and statistical ...
Pablo Belzarena, Laura Aspirot
JUCS
2007
95views more  JUCS 2007»
14 years 9 months ago
A First Step Mapping IMS Learning Design and Moodle
: Mapping the specification IMS Learning Design and the Course Management System Moodle is a logical step forward on interoperability between eLearning systems and specifications i...
Daniel Burgos, Colin Tattersall, Martin Dougiamas,...
ML
2007
ACM
144views Machine Learning» more  ML 2007»
14 years 9 months ago
Invariant kernel functions for pattern analysis and machine learning
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
Bernard Haasdonk, Hans Burkhardt
ICML
2007
IEEE
15 years 10 months ago
Information-theoretic metric learning
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...