Papers with positive sparsity problem

1 papers
Adaptive Scaling for Sparse Detection in Information Extraction (P18-1)

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Challenge: Detection problems involving positive instances are often deficient in information extraction tasks . a number of researches have employed neural network models to solve detection problems .
Approach: They propose an algorithm which can handle positive sparsity problem and directly optimize over F-measure . they borrow the idea of marginal utility from economics and propose a theoretical framework for instance importance measuring .
Outcome: The proposed algorithm improves on positive sparsity problem and over F-measure . it leads to more effective and stable training of neural network based detection models.

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