ZeroBN : learning compact neural networks for latency-critical edge systems

ZeroBN : learning compact neural networks for latency-critical edge systems

Edge devices have been widely adopted to bring deep learning applications onto low power embedded systems, mitigating the privacy and latency issues of accessing cloud servers. The increasingly computational demand of complex neural network models leads to large latency on edge devices with limited...

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Bibliographic Details
Main Authors: Huai, Shuo, Zhang, Lei, Liu, Di, Liu, Weichen, Subramaniam, Ravi
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2022
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
ZeroBN
Compact Learning
Online Access:https://hdl.handle.net/10356/155572

Internet

https://hdl.handle.net/10356/155572

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