25 citations · 29 across the 5 of their papers we have counts for
3 papers · 1 filter
Towards Out-of-Distribution Adversarial Robustness
Adam Ibrahim, Charles Guille-Escuret, Ioannis Mitliagkas +3
Adversarial robustness continues to be a major challenge for deep learning. A core issue is that robustness to one type of attack often fails to transfer to other attacks. While pr…
Learning Robust Kernel Ensembles with Kernel Average Pooling
Pouya Bashivan, Adam Ibrahim, Amirozhan Dehghani +1
Model ensembles have long been used in machine learning to reduce the variance in individual model predictions, making them more robust to input perturbations. Pseudo-ensemble meth…
Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound
Charles Guille-Escuret, Adam Ibrahim, Baptiste Goujaud +1
The study of first-order optimization is sensitive to the assumptions made on the objective functions. These assumptions induce complexity classes which play a key role in worst-ca…