8 citations · 25 across the 10 of their papers we have counts for
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cs.LG2021
Density-based interpretable hypercube region partitioning for mixed numeric and categorical data
Samuel Ackerman, Eitan Farchi, Orna Raz +2
Consider a structured dataset of features, such as . A user may want to know where in the feature space obser…
cs.LG2021
Machine Learning Model Drift Detection Via Weak Data Slices
Samuel Ackerman, Parijat Dube, Eitan Farchi +2
Detecting drift in performance of Machine Learning (ML) models is an acknowledged challenge. For ML models to become an integral part of business applications it is essential to de…
cs.LG2021
Broadly Applicable Targeted Data Sample Omission Attacks
Guy Barash, Eitan Farchi, Sarit Kraus +1
We introduce a novel clean-label targeted poisoning attack on learning mechanisms. While classical poisoning attacks typically corrupt data via addition, modification and omission,…