RFF-GP-HSMM speeds up unsupervised time-series segmentation by approximating Gaussian processes with random Fourier features, cutting computation time by up to 278 times on motion capture data with similar accuracy.
Weakly supervised action labeling in videos under ordering constraints,
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Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process
RFF-GP-HSMM speeds up unsupervised time-series segmentation by approximating Gaussian processes with random Fourier features, cutting computation time by up to 278 times on motion capture data with similar accuracy.