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» Selecting a Relevant Set of Examples to Learn IE-Rules
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ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
15 years 6 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
CSDA
2007
264views more  CSDA 2007»
14 years 11 months ago
Model-based methods to identify multiple cluster structures in a data set
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
Giuliano Galimberti, Gabriele Soffritti
CVPR
2010
IEEE
15 years 8 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
ICASSP
2009
IEEE
15 years 6 months ago
Annotating images by harnessing worldwide user-tagged photos
Automatic image tagging is important yet challenging due to the semantic gap and the lack of learning examples to model a tag’s visual diversity. Meanwhile, social user tagging ...
Xirong Li, Cees G. M. Snoek, Marcel Worring
ML
2008
ACM
134views Machine Learning» more  ML 2008»
14 years 11 months ago
Multilabel classification via calibrated label ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Johannes Fürnkranz, Eyke Hüllermeier, En...