12 citations · 35 across the 10 of their papers we have counts for
3 papers · 1 filter
fAux: Testing Individual Fairness via Gradient Alignment
Giuseppe Castiglione, Ga Wu, Christopher Srinivasa +1
Machine learning models are vulnerable to biases that result in unfair treatment of individuals from different populations. Recent work that aims to test a model's fairness at the…
Scalable Whitebox Attacks on Tree-based Models
Giuseppe Castiglione, Gavin Ding, Masoud Hashemi +2
Adversarial robustness is one of the essential safety criteria for guaranteeing the reliability of machine learning models. While various adversarial robustness testing approaches…
PUMA: Performance Unchanged Model Augmentation for Training Data Removal
Ga Wu, Masoud Hashemi, Christopher Srinivasa
Preserving the performance of a trained model while removing unique characteristics of marked training data points is challenging. Recent research usually suggests retraining a mod…