Learning Transfers via Transfer Learning
2021 IEEE Workshop on Innovating the Network for Data-Intensive Science (INDIS)(2021)
摘要
Detecting performance anomalies is key to efficiently utilize network resources and improve the quality of service. Researchers proposed various approaches to identify the presence of anomalies by analyzing performance statistics using heuristic (e.g., change point detection) and Machine Learning (ML) models. Although these models yield high accuracy in the networks that they are trained for, thei...
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关键词
Training,Analytical models,Transfer learning,Training data,Production,Throughput,Data models
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