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Quantization of Weights of Neural Networks with Negligible Decreasing of Prediction Accuracy
(Kaunas University of Technology, 2021-09-24)
Quantization and compression of neural network parameters using the uniform scalar quantization is carried out in this paper. The attractiveness of the uniform scalar quantizer is reflected in a low complexity and relatively ...
Design of a 2-Bit Neural Network Quantizer for Laplacian Source
(Molecular Diversity Preservation International, 2021-07-22)
Achieving real-time inference is one of the major issues in contemporary neural network applications, as complex algorithms are frequently being deployed to mobile devices that have constrained storage and computing power. ...
Binary Quantization Analysis of Neural Networks Weights on MNIST Dataset
(Kaunas University of Technology, 2021-08-23)
This paper considers the design of a binary scalar quantizer of Laplacian source and its application in compressed neural networks. The quantizer performance is investigated in a wide dynamic range of data variances, and ...