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ICML
2006
IEEE
14 years 8 months ago
MISSL: multiple-instance semi-supervised learning
There has been much work on applying multiple-instance (MI) learning to contentbased image retrieval (CBIR) where the goal is to rank all images in a known repository using a smal...
Rouhollah Rahmani, Sally A. Goldman
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 8 months ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
AAAI
2008
13 years 10 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
IEICET
2010
207views more  IEICET 2010»
13 years 6 months ago
A Semi-Supervised Approach to Perceived Age Prediction from Face Images
We address the problem of perceived age estimation from face images, and propose a new semi-supervised approach involving two novel aspects. The first novelty is an efficient act...
Kazuya Ueki, Masashi Sugiyama, Yasuyuki Ihara
SDM
2004
SIAM
225views Data Mining» more  SDM 2004»
13 years 9 months ago
Active Semi-Supervision for Pairwise Constrained Clustering
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Sugato Basu, Arindam Banerjee, Raymond J. Mooney