AutoForecast: Automatic Time-Series Forecasting Model Selection-Reference-Cited by-同舟云学术

AutoForecast: Automatic Time-Series Forecasting Model Selection

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Abdallah Mustafa¹,Rossi Ryan²,Mahadik Kanak²,Kim Sungchul²,Zhao Handong²,Bagchi Saurabh³

Affiliation:

1. Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA

2. Adobe Systems, San Jose, CA, USA

3. Purdue University, West Lafayette, IN, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557241

Reference60 articles.

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2. M. Abdallah , W. J. Lee , N. Raghunathan , C. Mousoulis , J. W. Sutherland , and S. Bagchi . Anomaly detection through transfer learning in agriculture and manufacturing iot systems. arXiv preprint arXiv:2102.05814 , 2021 . M. Abdallah, W. J. Lee, N. Raghunathan, C. Mousoulis, J. W. Sutherland, and S. Bagchi. Anomaly detection through transfer learning in agriculture and manufacturing iot systems. arXiv preprint arXiv:2102.05814, 2021.

3. Gluonts: Probabilistic and neural time series modeling in python;Alexandrov A.;J. Mach. Learn. Res.,2020

4. Combining and selecting forecasting models using rule based induction

5. On the use of cross-validation for time series predictor evaluation

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