Convex Clustering for Autocorrelated Time Series

Max Revay; Victor Solo

ICASSP 2022accepted0 citations

Convex Clustering for Autocorrelated Time Series

Abstract

While clustering in general is a heavily worked area, clustering of auto-correlated time series (CATS) has received relatively little attention. Here, we develop a convex clustering algorithm suited to auto-correlated time series and compare it with a state of the art method. We find the proposed algorithm is able to more accurately identify the true clusters.

BibTeX

@inproceedings{icassp2022_convexclustering,
  title = {Convex Clustering for Autocorrelated Time Series},
  author = {Max Revay and Victor Solo},
  booktitle = {ICASSP 2022},
  year = {2022}
}