no code implementations • 9 Nov 2019 • Marc Khoury
The geometry of the loss landscape is subtle and has important consequences for optimization algorithms.
no code implementations • 2 May 2019 • Marc Khoury, Dylan Hadfield-Menell
We show that adversarial training with Voronoi constraints produces robust models which significantly improve over the state-of-the-art on MNIST and are competitive on CIFAR-10.
no code implementations • ICLR 2019 • Marc Khoury, Dylan Hadfield-Menell
Adversarial examples are a pervasive phenomenon of machine learning models where seemingly imperceptible perturbations to the input lead to misclassifications for otherwise statistically accurate models.
1 code implementation • ICCV 2017 • Marc Khoury, Qian-Yi Zhou, Vladlen Koltun
We present an approach to learning features that represent the local geometry around a point in an unstructured point cloud.
Ranked #9 on Point Cloud Registration on ETH (trained on 3DMatch)