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In this paper we present a simple and computationally efficient quantization scheme that enables us to reduce the resolution of the parameters of a neural network from 32-bit floating point values to 8-bit integer values.
Y. Xie and M. A. Jabri, “Analysis of the effects of quantization in multilayer neural networks using a statistical model,”
1992
Earlier work this paper cites.
A. Gersho and R. M. Gray,
1992
Earlier work this paper cites.
G. Dündar and K. Rose, “The effects of quantization on multilayer neural networks,”
1995
Earlier work this paper cites.
A. C. Bovik,
2005
Earlier work this paper cites.
A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, “Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,” in
2006
Earlier work this paper cites.
K. Y. Tan and Y.-H. Leung, “Roundoff errors in fixed-point digital filters,” in
2008
Earlier work this paper cites.
B. Kingsbury, “Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling,” in
2009
Earlier work this paper cites.
V. Vanhoucke, A. Senior, and M. Mao, “Improving the speed of neural networks on cpus,” in
2011
Earlier work this paper cites.
E. Ozturk, J. Guilford, V. Gopal, and W. Feghali, “New instructions supporting large integer arithmetic on intel® architecture processors,” Intel Corporation, Tech. Rep., aug 2012
2012
Earlier work this paper cites.
X. Lei, A. Senior, A. Gruenstein, and J. Sorensen, “Accurate and compact large vocabulary speech recognition on mobile devices.” in
2013
Cited alongside, same era.
K. Hwang and W. Sung, “Fixed-point feedforward deep neural network design using weights -1, 0, and +1,” in
2014
Cited alongside, same era.
F. Seide, H. Fu, J. Droppo, G. Li, and D. Yu, “1-bit stochastic gradient descent and application to data-parallel distributed training of speech dnns,” in
2014
Cited alongside, same era.
2014
Cited alongside, same era.
2015
Later among the works it cites.
W. Sung, S. Shin, and K. Hwang, “Resiliency of deep neural networks under quantization,”
2015
Later among the works it cites.
H. Sak, A. Senior, K. Rao, and F. Beaufays, “Fast and accurate recurrent neural network acoustic models for speech recognition,” in
2015
Later among the works it cites.
2015
Later among the works it cites.
I. McGraw, R. Prabhavalkar, R. Alvarez, M. G. Arenas, K. Rao, D. Rybach, O. Alsharif, H. Sak, A. Gruenstein, F. Beaufays, and C. Parada, “Personalized speech recognition on mobile devices,” in
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2015
Cited alongside, same era.
O. Alsharif, T. Ouyang, F. Beaufays, S. Zhai, T. Breuel, and J. Schalkwyk, “Long short term memory neural network for keyboard gesture decoding,” in
2015
Cited alongside, same era.
2015
Cited alongside, same era.
2015
Cited alongside, same era.
2015
Cited alongside, same era.
2016
Closest in time.
H. Zen, Y. Agiomyrgiannakis, N. Egberts, F. Henderson, and P. Szczepaniak, “Optimizing lstm-rnn based statistical parametric speech synthesizers for production deployment,” in
2016
Closest in time.
M. Kim and P. Smaragdis, “Bitwise neural networks,”
2016
Closest in time.
R. Prabhavalkar, O. Alsharif, A. Bruguier, and I. McGraw, “On the compression of recurrent neural networks with an application to LVCSR acoustic modeling for embedded speech recognition,” in
2016
Closest in time.