AutoAI-TS

Author:

Shah Syed Yousaf1,Patel Dhaval1,Vu Long1,Dang Xuan-Hong1,Chen Bei2,Kirchner Peter1,Samulowitz Horst1,Wood David1,Bramble Gregory1,Gifford Wesley M.1,Ganapavarapu Giridhar1,Vaculin Roman1,Zerfos Petros1

Affiliation:

1. IBM Thomas J. Watson Research Center, Yorktown Heights , NY, USA

2. IBM Research, Dublin, Ireland

Publisher

ACM

Reference34 articles.

1. Unsupervised real-time anomaly detection for streaming data

2. Pourya Ayria. Accessed: 2020-08--17. A complete Machine Learning PipeLine. https://www.kaggle.com/pouryaayria/a-complete-ml-pipeline-tutorial-acu-86 . Pourya Ayria. Accessed: 2020-08--17. A complete Machine Learning PipeLine. https://www.kaggle.com/pouryaayria/a-complete-ml-pipeline-tutorial-acu-86 .

3. Facebook. Accessed: 2021-02--10. Prophet. https://facebook.github.io/prophet/. Facebook. Accessed: 2021-02--10. Prophet. https://facebook.github.io/prophet/.

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1. AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting;The VLDB Journal;2024-07-30

2. Anomaly analytics in data-driven machine learning applications;International Journal of Data Science and Analytics;2024-07-12

3. Dynamic Spatial-Temporal Embedding via Neural Conditional Random Field for Multivariate Time Series Forecasting;ACM Transactions on Spatial Algorithms and Systems;2024-06-27

4. AutoRL X: Automated Reinforcement Learning on the Web;ACM Transactions on Interactive Intelligent Systems;2024-06-03

5. ShrinkHPO: Towards Explainable Parallel Hyperparameter Optimization;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

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