SetConv: A New Approach for Learning from Imbalanced Data

EMNLP 2020, pp. 1284-1294, 2020.

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Abstract:

For many real-world classification problems, e.g., sentiment classification, most existing machine learning methods are biased towards the majority class when the Imbalance Ratio (IR) is high. To address this problem, we propose a set convolution (SetConv) operation and an episodic training strategy to extract a single representative for ...More

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