46 citations · 84 across the 11 of their papers we have counts for
3 papers · 1 filter
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences
Andreas Anastasiou, Angelos Papanastasiou
The extensive emergence of big data techniques has led to an increasing interest in the development of change-point detection algorithms that can perform well in a multivariate, po…
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments
Andreas Anastasiou, Alessandro Barp, François-Xavier Briol +11
Stein's method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin…
Detecting multiple generalized change-points by isolating single ones
Andreas Anastasiou, Piotr Fryzlewicz
We introduce a new approach, called Isolate-Detect (ID), for the consistent estimation of the number and location of multiple generalized change-points in noisy data sequences. Exa…