Recent arXiv preprints

Finding a Nash equilibrium of a random win-lose game in expected polynomial time

Andrea Collevecchio, Gábor Lugosi, Adrian Vetta, Rui-Ray Zhang

Beyond independent component analysis: identifiability and algorithms

Alvaro Ribot, Anna Seigal, Piotr Zwiernik

On the local well-posedness of randomly forced reaction-diffusion equations with $L^2$ initial data and a superlinear reaction term

Mohammud Foondun, Davar Khoshnevisan, Eulalia Nualart

Robust, sub-Gaussian mean estimators in metric spaces

Daniel Bartl, Gábor Lugosi, Roberto Imbuzeiro Oliveira, Zoraida F. Rico

Empirical Bayes for Data Integration

Paul Rognon-Vael, David Rossell

Bayesian Predictive Inference Beyond Martingales

Marco Battiston, Lorenzo Cappello

Factorization by extremal privacy mechanisms: new insights into efficiency

Chiara Amorino, Arnaud Gloter

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces

Gábor Lugosi, Marcos Matabuena

Fixed-Point Estimation of the Drift Parameter in Stochastic Differential Equations Driven by Rough Multiplicative Fractional Noise

Chiara Amorino, Laure Coutin, Nicolas Marie

A Bayesian framework for change-point detection with uncertainty quantification

Davis Berlind, Lorenzo Cappello, Oscar Hernan Madrid Padilla

Orthogonal eigenvectors and singular vectors of tensors

Alvaro Ribot, Anna Seigal, Piotr Zwiernik

Linear Bandits with Non-i.i.d. Noise

Baptiste Abélès, Eugenio Clerico, Hamish Flynn, Gergely Neu

Inverse Q-Learning Done Right: Offline Imitation Learning in $Q^π$-Realizable MDPs

Antoine Moulin, Gergely Neu, Luca Viano

Distances for Markov chains from sample streams

Sergio Calo, Anders Jonsson, Gergely Neu, Ludovic Schwartz, Javier Segovia-Aguas

Differential Machine Learning for Time Series Prediction

Akash Yadav, Eulalia Nualart

Improving variable selection properties by leveraging external data

Paul Rognon-Vael, David Rossell, Piotr Zwiernik

Fractional interacting particle system: drift parameter estimation via Malliavin calculus

Chiara Amorino, Ivan Nourdin, Radomyra Shevchenko

Multivariate Poisson approximation of joint subgraph counts in random graphs via size-biased couplings

Eulalia Nualart, Rui-Ray Zhang

Semi-parametric local variable selection under misspecification

David Rossell, Arnold Kisuk Kseung, Ignacio Saez, Michele Guindani

Bayesian variance change point detection with credible sets

Lorenzo Cappello, Oscar Hernan Madrid Padilla

Highlighted Publications (last 5 years)

Theory

Entropic covariance models

P. Zwiernik — Annals of Statistics, 2025

Polynomial rates via deconvolution for nonparametric estimation in McKean-Vlasov SDEs

C. Amorino, D. Belomestny, V. Pilipauskaite, M Podolskij, S. Zhou — Probab. Theory Relat. Fields, 2024

Instantaneous everywhere-blow-up of parabolic SPDEs

M. Foondun, D. Khoshnevisan, E. Nualart — Probab. Theory Relat. Fields, 2024

Non-independent component analysis

G. Mesters, P. Zwiernik — Annals of Statistics, 2024

Increasing paths in random temporal graphs

N. Broutin, N. Kamčev, G. Lugosi — Ann. Appl. Probab., 2024

Semi-parametric local variable selection under misspecification

D. Rossell, A. K. Kseung, I. Saez, M. Guindani — Biometrika, 2024

Efficient coalescent model for heterochronous data

L. Cappello, A. Véber, J. A. Palacios — JASA, 2024

Minimax rate for multivariate data under componentwise local differential privacy constraints

C. Amorino, A. Gloter — Annals of Statistics, 2023

Total positivity in multivariate extremes

F. Röttger, S. Engelke, P. Zwiernik — Annals of Statistics, 2023

Bayesian change-point detection with spike-and-slab priors

L. Cappello, O. H. Madrid Padilla, J. A. Palacios — J. Comput. Graph. Stat., 2023

Loss function selection and the use of improper models

J. Jewson, D. Rossell. J. R. Stat. Soc. B, 2022

Locally associated graphical models and mixed convex exponential families

S. Lauritzen, P. Zwiernik. Ann. Stat., 50 (5), 2022

Multivariate mean estimation with direction-dependent accuracy

G. Lugosi, S. Mendelson. J. Eur. Math. Soc., 2022

Broadcasting on random recursive trees

L. Addario-Berry, L. Devroye, G. Lugosi, V. Velona. Ann. Appl. Probab., 2022

Concentration of posterior probabilities and normalized L₀ criteria

D. Rossell. Bayesian Anal., 17 (2), 2022

Heterogeneous large datasets integration using Bayesian factor regression

A. Avalos-Pacheco, D. Rossell, R. Savage. Bayesian Anal., 17 (1), 2022

Adaptive Preferential Sampling in Phylodynamics

L. Cappello, J. A. Palacios. J. Comput. Graph. Stat., 31 (2), 2022

Learning partial correlation graphs by covariance queries

G. Lugosi, J. Truszkowski, V. Velona, P. Zwiernik. JMLR, 22 (203), 2021

Approximate Laplace approximations for scalable model selection

D. Rossell, O. Abril, A. Bhattacharya. J. R. Stat. Soc. B, 83 (4), 2021

Robust multivariate mean estimation: the optimality of trimmed mean

G. Lugosi, S. Mendelson. Ann. Stat., 2021

Total positivity in exponential families with application to binary variables

S. Lauritzen, C. Uhler, P. Zwiernik. Ann. Stat., 49 (3), 2021

Additive Bayesian variable selection under censoring and misspecification

D. Rossell, F. J. Rubio. Statist. Sci., 38 (1), 2021

Dependence in elliptical partial correlation graphs

D. Rossell, P. Zwiernik. Electron. J. Stat., 15 (2), 2021

Noise sensitivity of the top eigenvector of a Wigner matrix

C. Bordenave, G. Lugosi, N. Zhivotovskiy. Probab. Theory Relat. Fields, 2020

Risk minimization by median-of-means tournaments

G. Lugosi, S. Mendelson. J. Eur. Math. Soc., 2020

Benign overfitting in linear regression

P. L. Bartlett, P. L. Long, G. Lugosi, A. Tsigler. PNAS, 117 (48), 2020

Applications

Graphical model inference with external network data

J. Jewson, L. Li, L. Battaglia, S. Hansen, D. Rossell, P. Zwiernik — Biometrics, 2024

Statistical challenges in tracking the evolution of SARS-CoV-2

L. Cappello, J. Kim, S. Liu, J. A. Palacios — Statistical Science, 2022

Specification analysis for technology use and teenager well-being

C. Semken, D. Rossell — JRSS C, 2022

Multi-omic strategy for COVID-19 severity

V. Parikh et al., L. Cappello, M. Ashley — Nat. Commun., 2022

Characterizing MHC-I genotype predictive power for oncogenic mutation probability in cancer patients

L. Beauchemin, M. Slifker, D. Rossell, J. Font-Burgada. Immunoinformatics, Methods & Protocols, Springer (2020)

The selection and analysis of fatty-acid ratios in marine pelagic organisms

M. Graeve, M. Greenacre. Limnol. Oceanogr. Methods 18, 196-210 (2020)

Amalgamations are valid in compositional data analysis and their log-ratios have an inverse transform

M. Greenacre. Appl. Comput. Geosci. 5, 100017 (2020)

KairosMS: A new solution for processing hyphenated UH-resolution mass-spectrometry data

R. Gavard, H. Jones, D. Palacio Lozano, M. Thomas, D. Rossell, S. Spencer, M. Barrow. Anal. Chem. 92 (5), 3775-3786 (2020)

Editorial Service

Current editorial service

Gábor Lugosi: Annals of Applied Probability; Journal of Machine Learning Research; Probability Theory and Related Fields
Eulàlia Nualart: Stochastic Processes and their Applications
David Rossell: Bayesian Analysis, JASA: Theory & Methods
Piotr Zwiernik: Journal of the Royal Statistical Society – Series B; Biometrika; Algebraic Statistics; Scandinavian Journal of Statistics