1 citations · 1 across the 3 of their papers we have counts for
4 papers
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…
Nonlocal optimization of binary neural networks
Amir Khoshaman, Giuseppe Castiglione, Christopher Srinivasa
We explore training Binary Neural Networks (BNNs) as a discrete variable inference problem over a factor graph. We study the behaviour of this conversion in an under-parameterized…
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…
Parity Partition Coding for Sharp Multi-Label Classification
Christopher G. Blake, Giuseppe Castiglione, Christopher Srinivasa +1
The problem of efficiently training and evaluating image classifiers that can distinguish between a large number of object categories is considered. A novel metric, sharpness, is p…