先验与后验
计算机科学
机器学习
人工神经网络
人工智能
认识论
哲学
作者
Shengxiang Zhu,Craig Gutterman,Alan Diaz Montiel,Jiakai Yu,Marco Ruffini,Gil Zussman,Daniel C. Kilper
出处
期刊:Optical Fiber Communication Conference
日期:2020-01-01
被引量:20
标识
DOI:10.1364/ofc.2020.t4b.4
摘要
A hybrid machine learning (HML) model combining a-priori and a-posteriori knowledge is implemented and tested, which is shown to reduce the prediction error and training complexity, compared to an analytical or neural network learning model.
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