  In this paper, we will show an unprecedented method to accelerate training
and improve performance, which called random gradient (RG). This method can be
easier to the training of any model without extra calculation cost, we use
Image classification, Semantic segmentation, and GANs to confirm this method
can improve speed which is training model in computer vision. The central idea
is using the loss multiplied by a random number to random reduce the
back-propagation gradient. We can use this method to produce a better result in
Pascal VOC, Cifar, Cityscapes datasets.
