Papers with text classification neural networks

1 papers
Adversarial Reprogramming of Text Classification Neural Networks (D19-1)

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Challenge: Recent studies have shown that adversarial examples can cause a machine learning model to misclassify a sample from the classifier's input domain.
Approach: They propose a context-based vocabulary remapping method that performs a computationally inexpensive input transformation to reprogram a victim classification model for a new set of sequences.
Outcome: The proposed method performs a cost-effective input transformation to reprogram a model for a new set of sequences without altering the network architecture or parameters.

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