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Dynamic ConvNets on Tiny Devices via Nested Sparsity
[article]
2022
arXiv
pre-print
This work introduces a new training and compression pipeline to build Nested Sparse ConvNets, a class of dynamic Convolutional Neural Networks (ConvNets) suited for inference tasks deployed on resource-constrained devices at the edge of the Internet-of-Things. A Nested Sparse ConvNet consists of a single ConvNet architecture containing N sparse sub-networks with nested weights subsets, like a Matryoshka doll, and can trade accuracy for latency at run time, using the model sparsity as a dynamic
arXiv:2203.03324v1
fatcat:vcdq3h3ljzf6jcfoan7zdllphu