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» Results of the KDD'99 Classifier Learning
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ICML
1998
IEEE
14 years 9 months ago
Employing EM and Pool-Based Active Learning for Text Classification
This paper shows how a text classifier's need for labeled training documents can be reduced by taking advantage of a large pool of unlabeled documents. We modify the Query-by...
Andrew McCallum, Kamal Nigam
ECCV
2008
Springer
14 years 11 months ago
Multiple Component Learning for Object Detection
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
Boris Babenko, Pietro Perona, Piotr Dollár,...
ICPR
2004
IEEE
14 years 10 months ago
Signal Discrimination Using a Support Vector Machine for Genetic Syndrome Diagnosis
In this study, a support vector machine (SVM) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (FISH) images in order to diagnose...
Amit David, Boaz Lerner
CVPR
2003
IEEE
14 years 11 months ago
Bootstrapping SVM Active Learning by Incorporating Unlabelled Images for Image Retrieval
The performance of image retrieval with SVM active learning is known to be poor when started with few labelled images only. In this paper, the problem is solved by incorporating t...
Lei Wang, Kap Luk Chan, Zhihua Zhang
ICML
2005
IEEE
14 years 9 months ago
Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning
We introduce a novel approach to incorporating domain knowledge into Support Vector Machines to improve their example efficiency. Domain knowledge is used in an Explanation Based ...
Qiang Sun, Gerald DeJong