1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CY2026
Beyond Performance Disparities: A Three-Level Audit of Representational Harm in CelebA
Sieun Park, Yuanmo He
Large-scale facial datasets like CelebA are widely used in computer vision, yet the cultural biases embedded in their labels remain underexplored. Fairness research has distinguish…
cs.CR2024★ 1 cited
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
Marlon Tobaben, Hibiki Ito, Joonas Jälkö +2
Membership inference attacks (MIAs) are used to test practical privacy of machine learning models. MIAs complement formal guarantees from differential privacy (DP) under a more rea…