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IJCAI
2003
13 years 6 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
ML
2000
ACM
124views Machine Learning» more  ML 2000»
13 years 5 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
ICCV
2009
IEEE
14 years 10 months ago
Which Faces to Tag: Adding Prior Constraints into Active Learning
We introduce an algorithm that guides the user to tag faces in the best possible order during a face recognition assisted tagging scenario. In particular, we extend the active l...
Ashish Kapoor, Gang Hua, Amir Akbarzadeh and Simon...
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 5 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
CVPR
2007
IEEE
14 years 7 months ago
Learning Visual Representations using Images with Captions
Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
Ariadna Quattoni, Michael Collins, Trevor Darrell