NDLI: ORION: Online Regularized Multi-task Regression and Its Application to Ensemble Forecasting

Content Provider	IEEE Xplore Digital Library
Author	Xu, Jianpeng Tan, Pang-Ning Luo, Lifeng
Copyright Year	2014
Abstract	Ensemble forecasting is a well-known numerical prediction technique for modeling the evolution of nonlinear dynamic systems. The ensemble member forecasts are generated from multiple runs of a computer model, where each run is obtained by perturbing the starting condition or using a different model representation of the dynamic system. The ensemble mean or median is typically chosen as the consensus point estimate of the aggregated forecasts for decision making purposes. These approaches are limited in that they assume each ensemble member is equally skill ful and do not consider their inherent correlations. In this paper, we cast the ensemble forecasting task as an online, multi-task regression problem and present a framework called ORION to estimate the optimal weights for combining the ensemble members. The weights are updated using a novel online learning with restart strategy as new observation data become available. Experimental results on seasonal soil moisture predictions from 12 major river basins in North America demonstrate the superiority of the proposed approach compared to the ensemble median and other baseline methods.
Starting Page	1061
Ending Page	1066
File Size	258431
Page Count	6
File Format	PDF
ISSN	15504786
e-ISBN	9781479943029
DOI	10.1109/ICDM.2014.90
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Forecasting Computational modeling Equations Prediction algorithms Manganese Data models Ensemble Forecasting Online Multi-task Learning
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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