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» Learning from Multiple Sources of Inaccurate Data
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ESANN
2006
15 years 7 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
ICCV
2009
IEEE
16 years 11 months ago
Unlabeled data improves word prediction
Labeling image collections is a tedious task, especially when multiple labels have to be chosen for each image. In this paper we introduce a new framework that extends state of ...
Nicolas Loeff, Ali Farhadi, Ian Endres and David A...
ACL
2008
15 years 7 months ago
Trainable Generation of Big-Five Personality Styles through Data-Driven Parameter Estimation
Previous work on statistical language generation has primarily focused on grammaticality and naturalness, scoring generation possibilities according to a language model or user fe...
François Mairesse, Marilyn A. Walker
BMCBI
2004
112views more  BMCBI 2004»
15 years 6 months ago
Predicting co-complexed protein pairs using genomic and proteomic data integration
Background: Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same p...
Lan V. Zhang, Sharyl L. Wong, Oliver D. King, Fred...
SAC
2009
ACM
16 years 1 months ago
Enhancing XML data warehouse query performance by fragmentation
XML data warehouses form an interesting basis for decisionsupport applications that exploit heterogeneous data from multiple sources. However, XML-native database systems currentl...
Hadj Mahboubi, Jérôme Darmont