198 citations · 302 across the 4 of their papers we have counts for
4 papers
Stochastic Activation Pruning for Robust Adversarial Defense
Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton +4
Neural networks are known to be vulnerable to adversarial examples. Carefully chosen perturbations to real images, while imperceptible to humans, induce misclassification and threa…
StrassenNets: Deep Learning with a Multiplication Budget
Michael Tschannen, Aran Khanna, Anima Anandkumar
A large fraction of the arithmetic operations required to evaluate deep neural networks (DNNs) consists of matrix multiplications, in both convolution and fully connected layers. W…
Tensor Regression Networks
Jean Kossaifi, Zachary C. Lipton, Arinbjorn Kolbeinsson +3
Convolutional neural networks typically consist of many convolutional layers followed by one or more fully connected layers. While convolutional layers map between high-order activ…
Tensor Contraction Layers for Parsimonious Deep Nets
Jean Kossaifi, Aran Khanna, Zachary C. Lipton +2
Tensors offer a natural representation for many kinds of data frequently encountered in machine learning. Images, for example, are naturally represented as third order tensors, whe…