113 citations · 230 across the 8 of their papers we have counts for
3 papers · 1 filter
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
Jiong Zhang, Hsiang-fu Yu, Inderjit S. Dhillon
Deep neural networks have yielded superior performance in many applications; however, the gradient computation in a deep model with millions of instances lead to a lengthy training…
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Jiong Zhang, Qi Lei, Inderjit S. Dhillon
Vanishing and exploding gradients are two of the main obstacles in training deep neural networks, especially in capturing long range dependencies in recurrent neural networks~(RNNs…
Learning Long Term Dependencies via Fourier Recurrent Units
Jiong Zhang, Yibo Lin, Zhao Song +1
It is a known fact that training recurrent neural networks for tasks that have long term dependencies is challenging. One of the main reasons is the vanishing or exploding gradient…