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Deeply Vulnerable -- a study of the robustness of face recognition to presentation attacks

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Deeply Vulnerable -- a study of the robustness of face recognition to presentation attacks

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Deep Learning Generalization with Limited and Noisy Labels

Leveraging Unlabeled Data to Track Memorization

EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

The spectral bias of polynomial neural networks

On the robustness of randomized classifiers to adversarial examples

Deep Learning Generalization with Limited and Noisy Labels

Leveraging Unlabeled Data to Track Memorization

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Regularization of polynomial networks for image recognition

EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Regularization of polynomial networks for image recognition

On the robustness of randomized classifiers to adversarial examples

BLACK-BOX ATTACKS ON IMAGE ACTIVITY PREDICTION AND ITS NATURAL LANGUAGE EXPLANATIONS

The spectral bias of polynomial neural networks