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A cost-reducing partial labeling estimator in text classification problem
We propose a new approach to address the text classification problems when learning with partial labels is beneficial.
Centroid estimation based on symmetric KL divergence for Multinomial text classification problem
We define a new method to estimate centroid for text classification based on the symmetric KL-divergence between the distribution of words in training documents and their class centroids.
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