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SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
15 years 3 months ago
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
134
Voted
CVPR
2012
IEEE
13 years 4 months ago
Learning object class detectors from weakly annotated video
Object detectors are typically trained on a large set of still images annotated by bounding-boxes. This paper introduces an approach for learning object detectors from realworld w...
Alessandro Prest, Christian Leistner, Javier Civer...
BMCBI
2005
153views more  BMCBI 2005»
15 years 1 months ago
Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text
Background: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical ...
Soumya Ray, Mark Craven
PAMI
2007
187views more  PAMI 2007»
15 years 1 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
ACL
2008
15 years 3 months ago
Learning Document-Level Semantic Properties from Free-Text Annotations
This paper demonstrates a new method for leveraging unstructured annotations to infer semantic document properties. We consider the domain of product reviews, which are often anno...
S. R. K. Branavan, Harr Chen, Jacob Eisenstein, Re...