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» On Discriminative Semi-Supervised Classification
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AAAI
2008
13 years 7 months ago
On Discriminative Semi-Supervised Classification
The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels shoul...
Fei Wang, Changshui Zhang
ADMA
2009
Springer
246views Data Mining» more  ADMA 2009»
13 years 11 months ago
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a s...
Yan Gao, Ming Yang, Alok N. Choudhary
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
PAMI
2011
12 years 11 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
CVPR
2008
IEEE
14 years 6 months ago
Semi-Supervised Discriminant Analysis using robust path-based similarity
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
Yu Zhang, Dit-Yan Yeung