The computational complexity of deep neural networks is a major obstacle of many application scenarios driven by low-power devices, including federated learning. A recent finding shows that random sketches can substantially reduce the model complexity without affecting prediction accuracy.
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Wang, S. Efficient deep learning. Nat Comput Sci 1, 181–182 (2021). https://doi.org/10.1038/s43588-021-00042-x
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DOI: https://doi.org/10.1038/s43588-021-00042-x
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