We study properties of a sample covariance estimate Σ=
(𝐗_1 𝐗_1^⊤ + … + ...
Laplace approximation is a very useful tool in Bayesian inference and it...
This paper offers a new approach for study the frequentist properties of...
Due to the technological progress of the last decades, Community Detecti...
This note attempts to revisit the classical results on Laplace approxima...
The aim of online change-point detection is for a accurate, timely disco...
The aim of this note is to state a couple of general results about the
p...
Bures-Wasserstein barycenter is a popular and promising tool in analysis...
Prediction for high dimensional time series is a challenging task due to...
Least squares Monte Carlo methods are a popular numerical approximation
...
Bayesian methods are actively used for parameter identification and
unce...
We extend the theoretical study of a recently proposed nonparametric
clu...
The prominent Bernstein – von Mises (BvM) result claims that the posteri...
We consider a problem of manifold estimation from noisy observations. We...
In this work we introduce the concept of Bures-Wasserstein barycenter
Q_...
In this work we introduce a novel approach of construction of multivaria...
In this note we propose a new approach towards solving numerically optim...
IV regression in the context of a re-sampling is considered in the work....
In this work, we propose to define Gaussian Processes indexed by
multidi...
We consider a problem of multiclass classification, where the training s...
Let X_1, ..., X_n be i.i.d. sample in R^p with zero mean and
the covaria...
This paper presents a new approach to non-parametric cluster analysis ca...
Sparse non-Gaussian component analysis (SNGCA) is an unsupervised method...