Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
LearningBlack-BoxAttackers withTransferablePriorsandQueryFeedback
Neural Information Processing Systems
Inspired by consistency of visual saliency between different vision models, a surrogate model isexpected toimprovetheattack performance viatransferability.
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CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation
Neural Information Processing Systems
To meaningfully regularize the model's decision boundary, CODA introduces virtual unknown classes
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