45 citations · 47 across the 6 of their papers we have counts for
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cs.LG2023
Epsilon*: Privacy Metric for Machine Learning Models
Diana M. Negoescu, Humberto Gonzalez, Saad Eddin Al Orjany +9
We introduce Epsilon*, a new privacy metric for measuring the privacy risk of a single model instance prior to, during, or after deployment of privacy mitigation strategies. The me…
cs.LG2021★ 45 cited
Fast TreeSHAP: Accelerating SHAP Value Computation for Trees
Jilei Yang
SHAP (SHapley Additive exPlanation) values are one of the leading tools for interpreting machine learning models, with strong theoretical guarantees (consistency, local accuracy) a…