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Poisoning the Search Space in Neural Architecture Search
[article]
2021
arXiv
pre-print
Deep learning has proven to be a highly effective problem-solving tool for object detection and image segmentation across various domains such as healthcare and autonomous driving. At the heart of this performance lies neural architecture design which relies heavily on domain knowledge and prior experience on the researchers' behalf. More recently, this process of finding the most optimal architectures, given an initial search space of possible operations, was automated by Neural Architecture
arXiv:2106.14406v1
fatcat:djzxfy3kerei5mabmqg2o5a7va