activity
20182026
collaborators

13 papers

stat.ME2026

Graphical Models for Multivariate Count Data

Iza Danielewska, Bartosz Kołodziejek

The classical multinomial, negative multinomial, hypergeometric, and negative hypergeometric distributions are naturally organized by two features of the sampling scheme: sampling…

math.PR2026

Finite free perpetuities

Julia Le Bihan, Bartosz Kołodziejek

We introduce and study finite free perpetuities, defined as monic polynomial solutions of degree to the affine fixed-point equation \[ p(z) = \mathbb{E}\!\left[ A^{n}\,p\!\left…

math.PR2026

On the empirical spectral distribution of matrix perpetuities

Bartosz Kołodziejek, Kamil Szpojankowski

We study matrix perpetuities, that is, solutions to affine fixed-point equations of the form \[ \mathbf{X} \stackrel{d}{=} \mathbf{A}\,\mathbf{X} \,\mathbf{A}^\top+\mathbf{B},\qqua…

math.ST2026

A new class of colored Gaussian graphical models with explicit normalizing constants

Adam Chojecki, Piotr Graczyk, Hideyuki Ishi +1

We study Bayesian model selection in colored Gaussian graphical models (CGGMs), which combine sparsity of conditional independencies with symmetry constraints encoded by vertex- an…

math.ST2025

Identifying Network Hubs with the Partial Correlation Graphical LASSO

Małgorzata Bogdan, Adam Chojecki, Ivan Hejný +2

Graphical LASSO (GLASSO) is a widely used method for estimating sparse precision matrices and learning undirected graphical models in high-dimensional settings. Because GLASSO pena…

math.ST2025

From Graphical Lasso to Atomic Norms: High-Dimensional Pattern Recovery

Piotr Graczyk, Bartosz Kołodziejek, Hideto Nakashima +1

Estimating high-dimensional precision matrices is a fundamental problem in modern statistics, with the graphical lasso and its -penalty being a standard approach for recove…