1.9k citations · 5.6k across the 24 of their papers we have counts for
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cs.LG2016★ 1.1k cited
Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt +2
Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small difference between training and test performance. Conventional wisdom attribut…
cs.LG2016★ 516 cited
Training Deep Nets with Sublinear Memory Cost
Tianqi Chen, Bing Xu, Chiyuan Zhang +1
We propose a systematic approach to reduce the memory consumption of deep neural network training. Specifically, we design an algorithm that costs O(sqrt(n)) memory to train a n la…