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Safety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software Deployment. (arXiv:2208.05969v1 [cs.LG])
Aug. 15, 2022, 1:20 a.m. | Jie Zhu, Leye Wang, Xiao Han
cs.CR updates on arXiv.org arxiv.org
The size of deep learning models in artificial intelligence (AI) software is
increasing rapidly, which hinders the large-scale deployment on
resource-restricted devices (e.g., smartphones). To mitigate this issue, AI
software compression plays a crucial role, which aims to compress model size
while keeping high performance. However, the intrinsic defects in the big model
may be inherited by the compressed one. Such defects may be easily leveraged by
attackers, since the compressed models are usually deployed in a large number
of …
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