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A Quantitative Exploration of Collaborative Pruning and Approximation Computing Towards Energy Efficient Neural Networks

He, X; Yan, GH; Lu, WY; Zhang, X; Liu, K

He, X (corresponding author), Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA.

IEEE DESIGN & TEST, 2020; 37 (1): 36

Abstract

Editor's note: This work has the goal of minimizing digital neural network computation energy consumption with little loss in accuracy. The authors de......

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