85 citations · 285 across the 20 of their papers we have counts for
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cs.DC2018★ 1 cited
Data-parallel distributed training of very large models beyond GPU capacity
Samuel Matzek, Max Grossman, Minsik Cho +3
GPUs have limited memory and it is difficult to train wide and/or deep models that cause the training process to go out of memory. It is shown in this paper how an open source tool…
cs.LG2018★ 2 cited
A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks
Yuzhe Ma, Ran Chen, Wei Li +4
Deep neural networks (DNNs) have achieved significant success in a variety of real world applications, i.e., image classification. However, tons of parameters in the networks restr…
cond-mat.str-el2018★ 53 cited
Ab Initio Finite Temperature Auxiliary Field Quantum Monte Carlo
Yuan Liu, Minsik Cho, Brenda Rubenstein
We present an \textit{ab initio} auxiliary field quantum Monte Carlo method for studying the electronic structure of molecules, solids, and model Hamiltonians at finite temperature…