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IJCNN
2008
IEEE
13 years 10 months ago
Active Meta-Learning with Uncertainty Sampling and Outlier Detection
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
TASLP
2010
144views more  TASLP 2010»
12 years 10 months ago
Active Learning With Sampling by Uncertainty and Density for Data Annotations
To solve the knowledge bottleneck problem, active learning has been widely used for its ability to automatically select the most informative unlabeled examples for human annotation...
Jingbo Zhu, Huizhen Wang, Benjamin K. Tsou, Matthe...
NC
1998
102views Neural Networks» more  NC 1998»
13 years 5 months ago
Outliers and Bayesian Inference
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Peter Sykacek
CIDU
2010
13 years 1 months ago
Improving Cause Detection Systems with Active Learning
Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an...
Isaac Persing, Vincent Ng
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 1 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer