Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

arXiv: Learning, Volume abs/1803.04765, 2018.

Cited by: 201|Views48
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Abstract:

Deep neural networks (DNNs) enable innovative applications of machine learning like image recognition, machine translation, or malware detection. However, deep learning is often criticized for its lack of robustness in adversarial settings (e.g., vulnerability to adversarial inputs) and general inability to rationalize its predictions. In...More

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