256 citations · 457 across the 8 of their papers we have counts for
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stat.ML2019
Adversarial Robustness through Local Linearization
Chongli Qin, James Martens, Sven Gowal +6
Adversarial training is an effective methodology for training deep neural networks that are robust against adversarial, norm-bounded perturbations. However, the computational cost…
cs.LG2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
Karthik A. Sankararaman, Soham De, Zheng Xu +2
This paper studies how neural network architecture affects the speed of training. We introduce a simple concept called gradient confusion to help formally analyze this. When gradie…