%0 Generic %1 brock2017freezeout %A Brock, Andrew %A Lim, Theodore %A Ritchie, J. M. %A Weston, Nick %D 2017 %K 2017 arxiv deep-learning %T FreezeOut: Accelerate Training by Progressively Freezing Layers %U http://arxiv.org/abs/1706.04983 %X The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set portion of the training run, freezing them out one-by-one and excluding them from the backward pass. Through experiments on CIFAR, we empirically demonstrate that FreezeOut yields savings of up to 20% wall-clock time during training with 3% loss in accuracy for DenseNets, a 20% speedup without loss of accuracy for ResNets, and no improvement for VGG networks. Our code is publicly available at https://github.com/ajbrock/FreezeOut

@misc{brock2017freezeout, abstract = {The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set portion of the training run, freezing them out one-by-one and excluding them from the backward pass. Through experiments on CIFAR, we empirically demonstrate that FreezeOut yields savings of up to 20% wall-clock time during training with 3% loss in accuracy for DenseNets, a 20% speedup without loss of accuracy for ResNets, and no improvement for VGG networks. Our code is publicly available at https://github.com/ajbrock/FreezeOut}, added-at = {2018-06-10T09:51:53.000+0200}, author = {Brock, Andrew and Lim, Theodore and Ritchie, J. M. and Weston, Nick}, biburl = {https://www.bibsonomy.org/bibtex/20bec23d0fcbbf846cbca98e8b014bc33/achakraborty}, description = {[1706.04983] FreezeOut: Accelerate Training by Progressively Freezing Layers}, interhash = {31fb3f71a0ab68c915b1f4a3e6651c5c}, intrahash = {0bec23d0fcbbf846cbca98e8b014bc33}, keywords = {2017 arxiv deep-learning}, note = {cite arxiv:1706.04983Comment: Extended Abstract}, timestamp = {2018-06-10T09:52:06.000+0200}, title = {FreezeOut: Accelerate Training by Progressively Freezing Layers}, url = {http://arxiv.org/abs/1706.04983}, year = 2017 }