Mariele Motta

Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study

2020 · arXiv (Cornell University)

Despite achieving remarkable performance on many image classification tasks, state-of-the-art machine learning (ML) classifiers remain vulnerable to small input perturbations. Especially, the existence of adversarial examples raises concerns about the deployment of ML models in …