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most citedEMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware Classifiers

24 citations · 31 across the 5 of their papers we have counts for

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cs.LG2023

Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile

Tyler LeBlond, Joseph Munoz, Fred Lu +4

Differential privacy (DP) is the prevailing technique for protecting user data in machine learning models. However, deficits to this framework include a lack of clarity for selecti…