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Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search
[article]
2022
arXiv
pre-print
Neural networks often encounter various stringent resource constraints while deploying on edge devices. To tackle these problems with less human efforts, automated machine learning becomes popular in finding various neural architectures that fit diverse Artificial Intelligence of Things (AIoT) scenarios. Recently, to prevent the leakage of private information while enable automated machine intelligence, there is an emerging trend to integrate federated learning and neural architecture search
arXiv:2202.11490v1
fatcat:tkbiffmfmrdtjfmt3uq53ajpm4