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Adversarial Attacks on Binary Image Recognition Systems
Nevertheless, we generalize SCAR to design attacks that fool state-of-the-art check processing systems using unnoticeable perturbations that lead to misclassification of deposit amounts.
Predicting Choice with Set-Dependent Aggregation
Providing users with alternatives to choose from is an essential component in many online platforms, making the accurate prediction of choice vital to their success.
Label Propagation Networks
Graph networks have recently attracted considerable interest, and in particular in the context of semi-supervised learning.
Robust Classification of Financial Risk
To the best of our knowledge, this is the first study of adversarial attacks and defenses for deep learning in financial services.
