18 citations · 28 across the 2 of their papers we have counts for
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cs.LG2021★ 10 cited
KAISA: An Adaptive Second-Order Optimizer Framework for Deep Neural Networks
J. Gregory Pauloski, Qi Huang, Lei Huang +4
Kronecker-factored Approximate Curvature (K-FAC) has recently been shown to converge faster in deep neural network (DNN) training than stochastic gradient descent (SGD); however, K…
cs.LG2020
Convolutional Neural Network Training with Distributed K-FAC
J. Gregory Pauloski, Zhao Zhang, Lei Huang +2
Training neural networks with many processors can reduce time-to-solution; however, it is challenging to maintain convergence and efficiency at large scales. The Kronecker-factored…