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: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks.

Michaela BlottThomas B. PreußerNicholas J. FraserGiulio GambardellaKenneth O'BrienYaman UmurogluMiriam LeeserKees A. Vissers
Published in: ACM Trans. Reconfigurable Technol. Syst. (2018)
Keyphrases
  • end to end
  • deep learning
  • neural network
  • pattern recognition
  • unsupervised learning
  • feature space
  • viewpoint
  • probabilistic model
  • admission control