4 citations · 12 across the 7 of their papers we have counts for
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cs.LG2021★ 3 cited
A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, Wenjie Liu +2
A wide range of optimization problems arising in machine learning can be solved by gradient descent algorithms, and a central question in this area is how to efficiently compress a…
math.NA2021★ 3 cited
Learning optimal multigrid smoothers via neural networks
Ru Huang, Ruipeng Li, Yuanzhe Xi
Multigrid methods are one of the most efficient techniques for solving linear systems arising from Partial Differential Equations (PDEs) and graph Laplacians from machine learning…
cs.LG2021★ 2 cited
Generating a Doppelganger Graph: Resembling but Distinct
Yuliang Ji, Ru Huang, Jie Chen +1
Deep generative models, since their inception, have become increasingly more capable of generating novel and perceptually realistic signals (e.g., images and sound waves). With the…