Corpus ID: 29546424

Time-series Extreme Event Forecasting with Neural Networks at Uber

@inproceedings{Laptev2017TimeseriesEE,
  title={Time-series Extreme Event Forecasting with Neural Networks at Uber},
  author={Nikolay Pavlovich Laptev and Jason Yosinski and Li Erran Li and Slawek Smyl},
  year={2017}
}
Accurate time-series forecasting during high variance segments (e.g., holidays), is critical for anomaly detection, optimal resource allocation, budget planning and other related tasks. At Uber accurate prediction for completed trips during special events can lead to a more efficient driver allocation resulting in a decreased wait time for the riders. State of the art methods for handling this task often rely on a combination of univariate forecasting models (e.g., Holt-Winters) and machine… Expand

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