Hard Mining for Robust Classification
Published:
In this blog post we want to explore whether training mostly on the hardest examples allows us to fit robust networks on CIFAR-10 quicker.
Published:
In this blog post we want to explore whether training mostly on the hardest examples allows us to fit robust networks on CIFAR-10 quicker.
Published:
In our recent CVPR paper, “1-Lipschitz Layers Compared: Memory, Speed and Certifiable Robustness” we compared different methods of creating 1-Lipschitz convolutions. In this blog post we try to give some additional background on why 1-Lipschitz methods are an interesting research topic, and discuss some results from the paper.
Published:
In this blog post we want to explore whether training mostly on the hardest examples allows us to fit robust networks on CIFAR-10 quicker.
Published:
In our recent CVPR paper, “1-Lipschitz Layers Compared: Memory, Speed and Certifiable Robustness” we compared different methods of creating 1-Lipschitz convolutions. In this blog post we try to give some additional background on why 1-Lipschitz methods are an interesting research topic, and discuss some results from the paper.
Published:
In this blog post we want to explore whether training mostly on the hardest examples allows us to fit robust networks on CIFAR-10 quicker.