Search Results for author:
Found 5 papers, 2 papers with code
Limitations of Face Image Generation
In particular, their ability to synthesize and modify human faces has spurred research into using generated face images in both training data augmentation and model performance assessments.
An Exploration of Multicalibration Uniform Convergence Bounds
Given the prevalence of ERM sample complexity bounds, our proposed framework enables machine learning practitioners to easily understand the convergence behavior of multicalibration error for a myriad of classifier architectures.
Fairness Properties of Face Recognition and Obfuscation Systems
We answer this question with an analytical and empirical exploration of recent face obfuscation systems.
Analyzing Accuracy Loss in Randomized Smoothing Defenses
In test-time attacks an adversary crafts adversarial examples, which are specially crafted perturbations imperceptible to humans which, when added to an input example, force a machine learning model to misclassify the given input example.
A Geometric Perspective on the Transferability of Adversarial Directions
We show that these "transferable adversarial directions" are guaranteed to exist for linear separators of a given set, and will exist with high probability for linear classifiers trained on independent sets drawn from the same distribution.
