This paper considers binary classification of high-dimensional features ...
In high-dimensional classification problems, a commonly used approach is...
This paper studies the estimation of high-dimensional, discrete, possibl...
High-dimensional feature vectors are likely to contain sets of measureme...
This work is devoted to the finite sample prediction risk analysis of a ...
This work studies finite-sample properties of the risk of the minimum-no...
Topic models have become popular tools for dimension reduction and
explo...
Essential Regression is a new type of latent factor regression model, wh...
We propose a new method of estimation in topic models, that is not a
var...
The problem of overlapping variable clustering, ubiquitous in data scien...
We study the adaptive estimation of copula correlation matrix Σ for
the ...
We consider the problem of binary classification where one can, for a
pa...