Robust Time Series Analysis and Applications-Reference-Cited by-同舟云学术

Robust Time Series Analysis and Applications

Published:2022-08-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Wen Qingsong¹,Yang Linxiao²,Zhou Tian²,Sun Liang¹

Affiliation:

1. Alibaba Group, Bellevue, WA, USA

2. Alibaba Group, Hangzhou, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3542612

Reference35 articles.

1. Fourier Analysis of Time Series

2. Stephen Boyd Neal Parikh Eric Chu Borja Peleato Jonathan Eckstein etal 2011. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends® in Machine learning Vol. 3 1 (2011). Stephen Boyd Neal Parikh Eric Chu Borja Peleato Jonathan Eckstein et al. 2011. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends® in Machine learning Vol. 3 1 (2011).

3. Learning to Rotate

4. STL: A Seasonal-Trend Decomposition Procedure Based on Loess;Cleveland Robert B;Journal of Official Statistics,1990

5. Jingkun Gao , Xiaomin Song , Qingsong Wen , Pichao Wang , Liang Sun , and Huan Xu . 2020 . RobustTAD: Robust time series anomaly detection via decomposition and convolutional neural networks . KDD Workshop MileTS (2020). Jingkun Gao, Xiaomin Song, Qingsong Wen, Pichao Wang, Liang Sun, and Huan Xu. 2020. RobustTAD: Robust time series anomaly detection via decomposition and convolutional neural networks. KDD Workshop MileTS (2020).

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