%0 Journal Article %1 ramanujan2019whats %A Ramanujan, Vivek %A Wortsman, Mitchell %A Kembhavi, Aniruddha %A Farhadi, Ali %A Rastegari, Mohammad %D 2019 %K deep-learning generalization readings theory %T What's Hidden in a Randomly Weighted Neural Network? %U http://arxiv.org/abs/1911.13299 %X Training a neural network is synonymous with learning the values of the weights. In contrast, we demonstrate that randomly weighted neural networks contain subnetworks which achieve impressive performance without ever training the weight values. Hidden in a randomly weighted Wide ResNet-50 we show that there is a subnetwork (with random weights) that is smaller than, but matches the performance of a ResNet-34 trained on ImageNet. Not only do these üntrained subnetworks" exist, but we provide an algorithm to effectively find them. We empirically show that as randomly weighted neural networks with fixed weights grow wider and deeper, an üntrained subnetwork" approaches a network with learned weights in accuracy.

@article{ramanujan2019whats, abstract = {Training a neural network is synonymous with learning the values of the weights. In contrast, we demonstrate that randomly weighted neural networks contain subnetworks which achieve impressive performance without ever training the weight values. Hidden in a randomly weighted Wide ResNet-50 we show that there is a subnetwork (with random weights) that is smaller than, but matches the performance of a ResNet-34 trained on ImageNet. Not only do these "untrained subnetworks" exist, but we provide an algorithm to effectively find them. We empirically show that as randomly weighted neural networks with fixed weights grow wider and deeper, an "untrained subnetwork" approaches a network with learned weights in accuracy.}, added-at = {2019-12-03T21:25:43.000+0100}, author = {Ramanujan, Vivek and Wortsman, Mitchell and Kembhavi, Aniruddha and Farhadi, Ali and Rastegari, Mohammad}, biburl = {https://www.bibsonomy.org/bibtex/2f0ca99849dc75c9b5d8f73f0540a8757/kirk86}, description = {[1911.13299] What's Hidden in a Randomly Weighted Neural Network?}, interhash = {598d920eee2746ce49f312ad3ee962e4}, intrahash = {f0ca99849dc75c9b5d8f73f0540a8757}, keywords = {deep-learning generalization readings theory}, note = {cite arxiv:1911.13299}, timestamp = {2019-12-03T21:25:43.000+0100}, title = {What's Hidden in a Randomly Weighted Neural Network?}, url = {http://arxiv.org/abs/1911.13299}, year = 2019 }