阿里巴巴集团于1999年创立,阿里巴巴集团子公司及关联公司有:阿里巴巴网络有限公司、淘宝网、淘宝商城(天猫)、一淘、支付宝、阿里云计算、中国雅虎等。

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题目: AI Compiler @Alibaba

目录:

  • AI编译器堆栈
  • 阿里巴巴如何使用TVM
  • TVM + AIService:PAI-Blade
  • 对TVM社区的贡献
  • 对社区的持续努力
  • 产品驱动的TVM增强
  • TVM带来了更多的性能
  • AliOS增强了车辆上的TVM
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最新论文

Periodicity detection is an important task in time series analysis as it plays a crucial role in many time series tasks such as classification, clustering, compression, anomaly detection, and forecasting. It is challenging due to the following reasons: 1, complicated non-stationary time series; 2, dynamic and complicated periodic patterns, including multiple interlaced periodic components; 3, outliers and noises. In this paper, we propose a robust periodicity detection algorithm to address these challenges. Our algorithm applies maximal overlap discrete wavelet transform to transform the time series into multiple temporal-frequency scales such that different periodicities can be isolated. We rank them by wavelet variance and then at each scale, and then propose Huber-periodogram by formulating the periodogram as the solution to M-estimator for introducing robustness. We rigorously prove the theoretical properties of Huber-periodogram and justify the use of Fisher's test on Huber-periodogram for periodicity detection. To further refine the detected periods, we compute unbiased autocorrelation function based on Wiener-Khinchin theorem from Huber-periodogram for improved robustness and efficiency. Experiments on synthetic and real-world datasets show that our algorithm outperforms other popular ones for both single and multiple periodicity detection. It is now implemented and provided as a public online service at Alibaba Group and has been used extensive in different business lines.

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