BranchyNet: Fast inference via early exiting from deep neural networks

Deep neural networks are state of the art methods for many learning tasks due to their ability to extract increasingly better features at each network layer. However, the improved performance of additional layers in a deep network comes at the cost of added latency and energy usage in feedforward in...

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Veröffentlicht in:	2016 23rd International Conference on Pattern Recognition (ICPR) S. 2464 - 2469
Hauptverfasser:	Teerapittayanon, Surat, McDanel, Bradley, Kung, H. T.
Format:	Tagungsbericht
Sprache:	Englisch Japanisch
Veröffentlicht:	IEEE 01.12.2016
Schlagworte:	Entropy Feedforward neural networks Inference algorithms Optimization Runtime Training
Online-Zugang:	Volltext
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