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PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++

PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++

Jae-Su Song
Fangzhen Lin
    MQ
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Papers citing "PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++"

5 / 5 papers shown
Title
Scalable Methods for 8-bit Training of Neural Networks
Scalable Methods for 8-bit Training of Neural Networks
Ron Banner
Itay Hubara
Elad Hoffer
Daniel Soudry
MQ
84
339
0
25 May 2018
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
Benoit Jacob
S. Kligys
Bo Chen
Menglong Zhu
Matthew Tang
Andrew G. Howard
Hartwig Adam
Dmitry Kalenichenko
MQ
145
3,121
0
15 Dec 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
276
8,878
0
25 Aug 2017
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Mohammad Rastegari
Vicente Ordonez
Joseph Redmon
Ali Farhadi
MQ
161
4,353
0
16 Mar 2016
Binarized Neural Networks
Itay Hubara
Daniel Soudry
Ran El-Yaniv
MQ
187
1,348
0
08 Feb 2016