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ECIR
2009
Springer
11 years 5 months ago
Active Learning Strategies for Multi-Label Text Classification
Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...
Andrea Esuli, Fabrizio Sebastiani
ICTAI
2010
IEEE
11 years 6 months ago
Instance-Based Ensemble Pruning via Multi-Label Classification
Ensemble pruning is concerned with the reduction of the size of an ensemble prior to its combination. Its purpose is to reduce the space and time complexity of the ensemble and/or ...
Fotini Markatopoulou, Grigorios Tsoumakas, Ioannis...
AAAI
2012
9 years 10 months ago
Multi-Label Learning by Exploiting Label Correlations Locally
It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the ...
Sheng-Jun Huang, Zhi-Hua Zhou
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
12 years 8 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
CVPR
2009
IEEE
1599views Computer Vision» more  CVPR 2009»
13 years 3 months ago
Multi-Label Sparse Coding for Automatic Image Annotation
In this paper, we present a multi-label sparse coding framework for feature extraction and classification within the context of automatic image annotation. First, each image is ...
Changhu Wang (University of Science and Technology...
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