Training Multi-Bit Quantized and Binarized Networks with a Learnable Symmetric Quantizer

Training Multi-Bit Quantized and Binarized Networks with a Learnable Symmetric Quantizer

Quantizing weights and activations of deep neural networks is essential for deploying them in resource-constrained devices, or cloud platforms for at-scale services. While binarization is a special case of quantization, this extreme case often leads to several training difficulties, and necessitates...

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Bibliographic Details
Main Authors: Phuoc Pham, Jacob A. Abraham, Jaeyong Chung
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Learnable quantizer
quantization
binarization
model compression
machine learning
neuromorphic computing
Online Access:https://ieeexplore.ieee.org/document/9383003/

Internet

https://ieeexplore.ieee.org/document/9383003/

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