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» Learning SVMs from Sloppily Labeled Data
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ICCV
2009
IEEE
15 years 2 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...
ISMIS
1999
Springer
14 years 1 months ago
Machine Learning Method for Software Quality Model Building
Software quality prediction can be cast as a concept learning problem. In this paper, we discuss the full cycle of an application of Machine Learning to software quality predictio...
Mauricio Amaral de Almeida, Stan Matwin
ECCV
2000
Springer
14 years 11 months ago
Learning to Recognize 3D Objects with SNoW
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
ACL
2006
13 years 10 months ago
Machine Learning of Temporal Relations
This paper investigates a machine learning approach for temporally ordering and anchoring events in natural language texts. To address data sparseness, we used temporal reasoning ...
Inderjeet Mani, Marc Verhagen, Ben Wellner, Chong ...
JUCS
2008
139views more  JUCS 2008»
13 years 9 months ago
A Progressive Learning Method for Symbol Recognition
: This paper deals with a progressive learning method for symbol recognition which improves its own recognition rate when new symbols are recognized in graphic documents. We propos...
Sabine Barrat, Salvatore Tabbone