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KDD
2002
ACM
179views Data Mining» more  KDD 2002»
15 years 10 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
CVPR
2009
IEEE
15 years 1 months ago
Classification of tensors and fiber tracts using Mercer-kernels encoding soft probabilistic spatial and diffusion information
In this paper, we present a kernel-based approach to the clustering of diffusion tensors and fiber tracts. We propose to use a Mercer kernel over the tensor space where both spati...
Radhouène Neji, Nikos Paragios, Gilles Fleu...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
NN
2008
Springer
201views Neural Networks» more  NN 2008»
14 years 9 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
ANNPR
2008
Springer
14 years 12 months ago
Partial Discriminative Training of Neural Networks for Classification of Overlapping Classes
In applications such as character recognition, some classes are heavily overlapped but are not necessarily to be separated. For classification of such overlapping classes, either d...
Cheng-Lin Liu