A. Martínez-Finkelshtein

works on

incremental learning 1 kernel methods 1 mixture models 1 probability density estimation 1 radial basis functions 1

From the 1 of 4 linked papers with an AI index.

activity

20242026

collaborators

4 papers

math.ST2026

Compactly supported radial basis functions as probability density functions

Sergio DÃaz-Elbal, Andrei MartÃnez-Finkelshtein, DarÃo Ramos-LÃ³pez

The paper proposes using compactly supported radial basis functions, especially Wendland C² kernels, as a new parametric family of probability density functions and develops method…

math.CA2025

Flow of the zeros of polynomials under iterated differentiation

Andrei Martinez-Finkelshtein, Evgenii A. Rakhmanov

For a monic polynomial $Q_{n}$ of degree $n$ , let $Q_{n, k}$ be its $k$ -th derivative normalized to be monic. Under the only assumption that the sequence ${Q_{n}}$ has a weak* limiti…

math.CA2025

Weighted equilibrium and the flow of derivatives of polynomials

Andrei Martinez-Finkelshtein, Evgenii A. Rakhmanov

Given a sequence of polynomials $Q_{n}$ of degree $n$ with zeros on $[- 1, 1]$ , we consider the triangular table of derivatives $Q_{n, k} (x) = d^{k} Q_{n} (x) / d x^{k}$ . Under the assumption th…

math.CA2024

Real roots of hypergeometric polynomials via finite free convolution

Andrei Martinez-Finkelshtein, Rafael Morales, Daniel Perales

We examine two binary operations on the set of algebraic polynomials, known as multiplicative and additive finite free convolutions, specifically in the context of hypergeometric p…