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"Towards Best Possible Deep Learning Acceleration on the Edge", Yanzhi Wang, Northeastern University
[REFAI Seminar 03/02/21] Towards Best Possible Deep Learning Acceleration on the Edge
Towards Best Possible DL Acceleration on the Edge - A Compression-Compilation Co-Design Framework
June 2021 CACM: CoCoPIE
Northeastern Application Video
ASPLOS'20 - Session 10B - PatDNN: Achieving Real-Time DNN Execution on Mobile Devices
Pruning without data! - A Privacy-aware DNN Pruning and Mobile Acceleration
Model Compression vs. Robustness of DNNs -- Can We Have Both? (Yanzhi Wang, FSL Workshop)
SympleGraph - Distributed Graph Processing with Precise Loop Carried Dependency G
Learn-Prune-Share for Lifelong Learning
Oral Paper: CVPR'21 - NPAS: A Compiler-aware Framework for Beyond Real-Time Mobile Acceleration
Yanzhi Wang - Design, Control, and Applications of Photovoltaic Systems
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