• Corpus ID: 231846902

Few-shot time series segmentation using prototype-defined infinite hidden Markov models

@article{Qarout2021FewshotTS,
  title={Few-shot time series segmentation using prototype-defined infinite hidden Markov models},
  author={Yazan Qarout and Yordan P. Raykov and Max A. Little},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.03885}
}
We propose a robust framework for interpretable, few-shot analysis of non-stationary sequential data based on flexible graphical models to express the structured distribution of sequential events, using prototype radial basis function (RBF) neural network emissions. A motivational link is demonstrated between prototypical neural network architectures for few-shot learning and the proposed RBF network infinite hidden Markov model (RBF-iHMM). We show that RBF networks can be efficiently specified… 
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