Papers by Sam Altschul

1 papers
Metric Learning for Dynamic Text Classification (D19-61)

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Challenge: Traditional text classifiers are limited to predicting over a fixed set of labels, but real-world applications require dynamic classification.
Approach: They propose to replace the traditional fixed-size output layer with a learned metric space . they propose to add or remove support points in the metric and fine-tune the resulting metric .
Outcome: The proposed method is robust to changes in the label space and improves performance in low data regime.

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