Real-time payment fraud detection is a non-stationary streaming prediction problem: adversaries adapt before supervised labels mature, and localized burst attacks can cause losses before retraining. Production systems typically rely on tabular classifiers and rules, which can struggle to capture these emerging sequenti...
As machine learning (ML) algorithms are increasingly used in high-stakes applications, concerns have arisen that they may be biased against certain social groups. Although many approaches have been proposed to make ML models fair, they typically rely on the assumption that data distributions in training and deployment...
A systematic study of how pruning affects SAE behavior is presented and theoretically shows that, for a fixed SAE, its impact is governed by perturbation energy, a covariance-weighted norm.
Suchit Gupte, Xue-Ru Zhang, M. Khalili· 0 citations
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