research
∙
05/07/2023
Wasserstein distance bounds on the normal approximation of empirical autocovariances and cross-covariances under non-stationarity and stationarity
The autocovariance and cross-covariance functions naturally appear in ma...
share
research
∙
11/13/2022
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences
The extensive emergence of big data techniques has led to an increasing ...
research
∙
02/24/2022
Detecting change-points in noisy GPS time series with continuous piecewise structures
Detecting change-points in noisy data sequences with an underlying conti...
research
∙
05/07/2021
Stein's Method Meets Statistics: A Review of Some Recent Developments
Stein's method is a collection of tools for analysing distributional com...
research
∙
10/05/2020
Modeling of Covid-19 Pandemic in Cyprus
The Republic of Cyprus is a small island in the southeast of Europe and ...
research
∙
05/11/2020
Wasserstein distance error bounds for the multivariate normal approximation of the maximum likelihood estimator
We obtain explicit Wasserstein distance error bounds between the distrib...
research
∙
04/03/2019
Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT
We provide non-asymptotic convergence rates of the Polyak-Ruppert averag...
research
∙
01/30/2019
Detecting multiple generalized change-points by isolating single ones
We introduce a new approach, called Isolate-Detect (ID), for the consist...
research
∙
06/10/2018
