Data reduction through optimized scalar quantization for more compact neural networks

Data reduction through optimized scalar quantization for more compact neural networks

Raw data generation for several existing and planned large physics experiments now exceeds TB/s rates, generating untenable data sets in very little time. Those data often demonstrate high dimensionality while containing limited information. Meanwhile, Machine Learning algorithms are now becoming an...

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Bibliographic Details
Main Authors: Berthié Gouin-Ferland, Ryan Coffee, Audrey C. Therrien
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Physics
Subjects:
machine learning - ML
neural network
quantization
classification
free electron lasers
data acquisition
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2022.957128/full

Internet

https://www.frontiersin.org/articles/10.3389/fphy.2022.957128/full

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