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fairDMS: Rapid Model Training by Data and Model Reuse. (arXiv:2204.09805v2 [cs.LG] UPDATED)
Web: http://arxiv.org/abs/2204.09805
May 5, 2022, 1:12 a.m. | Ahsan Ali, Hemant Sharma, Rajkumar Kettimuthu, Peter Kenesei, Dennis Trujillo, Antonino Miceli, Ian Foster, Ryan Coffee, Jana Thayer, Zhengchun Liu
cs.LG updates on arXiv.org arxiv.org
Extracting actionable information from data sources such as the Linac
Coherent Light Source (LCLS-II) and Advanced Photon Source Upgrade (APS-U) is
becoming more challenging due to the fast-growing data generation rate. The
rapid analysis possible with ML methods can enable fast feedback loops that can
be used to adjust experimental setups in real-time, for example when errors
occur or interesting events are detected. However, to avoid degradation in ML
performance over time due to changes in an instrument or sample, …
More from arxiv.org / cs.LG updates on arXiv.org
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