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» Visualization of Labeled Data Using Linear Transformations
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ICASSP
2011
IEEE
13 years 2 months ago
Semi-supervised handwritten digit recognition using very few labeled data
We propose a novel semi-supervised classifier for handwritten digit recognition problems that is based on the assumption that any digit can be obtained as a slight transformation...
Steven Van Vaerenbergh, Ignacio Santamaría,...
CVPR
2006
IEEE
15 years 26 days ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
CIDM
2007
IEEE
14 years 5 months ago
Privacy Preserving Burst Detection of Distributed Time Series Data Using Linear Transforms
— In this paper, we consider burst detection within the context of privacy. In our scenario, multiple parties want to detect a burst in aggregated time series data, but none of t...
Lisa Singh, Mehmet Sayal
WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
14 years 5 months ago
Generating labels from clicks
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...
CVPR
2008
IEEE
15 years 26 days ago
Semi-supervised boosting using visual similarity learning
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Christian Leistner, Helmut Grabner, Horst Bischof