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Improving LBFGS optimizer in PyTorch: Knowledge transfer from radio interferometric calibration to machine learning

机译：改进Pytorch中的LBFGS优化器：从无线电干涉校准到机器学习的知识转移

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摘要

We have modified the LBFGS optimizer in PyTorch based on our knowledge in using the LBFGS algorithm in radio interferometric calibration (SAGECal). We give results to show the performance improvement of PyTorch in various machine learning applications due to our improvements.

机译：根据我们的知识在使用无线电干涉校准（SageCal）中的LBFGS算法，我们在Pytorch中修改了LBFGS优化器。由于我们的改进，我们将出现结果显示Pytorch在各种机器学习应用中的性能提高。

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《IEEE International Conference on e-Science》|2018年|xxxii 504 p. :|共2页
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作者
Sarod Yatawatta; Hanno Spreeuw; Faruk Diblen;
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中图分类 TP302.1-532;
关键词
LBFGS; Machine Learning; Radio Interferom-etry;

机译：BFGS;机器学习;无线电干涉测量;

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4. Improving LBFGS optimizer in PyTorch: Knowledge transfer from radio interferometric calibration to machine learning [C] . Sarod Yatawatta, Hanno Spreeuw, Faruk Diblen IEEE International Conference on e-Science . 2018

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Improving LBFGS optimizer in PyTorch: Knowledge transfer from radio interferometric calibration to machine learning

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