Fast, Better Training Trick -- Random Gradient
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 13 Aug 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1.
1 paper.