AMC: AutoML for Model Compression and Acceleration on Mobile Devices

ECCV 2018 Yihui HeJi LinZhijian LiuHanrui WangLi-Jia LiSong Han

Model compression is a critical technique to efficiently deploy neural network models on mobile devices which have limited computation resources and tight power budgets. Conventional model compression techniques rely on hand-crafted heuristics and rule-based policies that require domain experts to explore the large design space trading off among model size, speed, and accuracy, which is usually sub-optimal and time-consuming... (read more)

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