The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making

arXiv:2301.08970v2 Announce Type: replace
Abstract: The Cauchy-Schwarz (CS) divergence was developed by Pr\'{i}ncipe et al. in 2000. In this paper, we extend the classic CS divergence to quantify the closeness between two conditional distributions and show that the developed conditional CS divergence can be simply estimated by a kernel density estimator from given samples. We illustrate the advantages (e.g., rigorous faithfulness guarantee, lower computational complexity, higher statistical power, and much more flexibility in a wide range of applications) of our …

abstract applications arxiv cs.it cs.lg data decision decision making divergence making math.it paper series show stat.ml type