• The ensemble approach to forecasting: A review and synthesis 

      Wu, Hao; Levinson, David M.
      Published 2021
      Ensemble forecasting is a modeling approach that combines data sources, models of different types, with alternative assumptions, using distinct pattern recognition methods. The aim is to use all available information in ...
      Open Access
      Article
    • Adversarial Recurrent Time Series Imputation 

      Shuo, Yang; Dong, Minjing; Wang, Yunhe; Xu, Chang
      Published 2020
      For the real-world time series analysis, data missing is a ubiquitously existing problem due to anomalies during data collecting and storage. If not treated properly, this problem will seriously hinder the classification, ...
      Open Access
      Article
    • Iterative Privileged Learning 

      Li, Xue; Du, Bo; Zhang, Yipeng; Xu, Chang; Tao, Dacheng
      Published 2020
      While in the learning using privileged information paradigm, privileged information may not be as informative as example features in the context of making accurate label predictions, it may be able to provide some effective ...
      Open Access
      Article
    • Robust learning with imperfect privileged information 

      Li, Xue; Du, Bo; Xu, Chang; Zhang, Yipeng; Zhang, Lefei; Tao, Dacheng
      Published 2020
      In the learning using privileged information (LUPI) paradigm, example data cannot always be clean, while the gathered privileged information can be imperfect in practice. Here, imperfect privileged information can refer ...
      Open Access
      Article
    • Self-supervised Pose Adaptation for Cross-Domain Image Animation 

      Wang, Chaoyue; Xu, Chang; Tao, Dacheng
      Published 2020
      Image animation is to animate a still image of the object of interest using poses extracted from another video sequence. Through training on a large-scale video dataset, most existing approaches aim to explore disentangled ...
      Open Access
      Article