Nonparametric Bayes and empirical Bayes for species sampling problems: classical questions, new directions and related issues

Publikacje

On Johnson’s “Sufficientness” Postulates for Feature-Sampling Models

Autorzy: Federico Camerlenghi, Stefano Favaro
Opublikowane w: Mathematics, 2021, ISSN 2227-7390
Wydawca: MDPI
DOI: 10.3390/math9222891

Upscaling human activity data: A statistical ecology approach

Autorzy: Anna Tovo, Samuele Stivanello, Amos Maritan, Samir Suweis, Stefano Favaro, Marco Formentin
Opublikowane w: PLOS ONE, Numer 16/7, 2021, Strona(/y) e0253461, ISSN 1932-6203
Wydawca: Public Library of Science
DOI: 10.1371/journal.pone.0253461

Bayesian nonparametric disclosure risk assessment

Autorzy: Stefano Favaro, Francesca Panero, Tommaso Rigon
Opublikowane w: Electronic Journal of Statistics, 2021, ISSN 1935-7524
Wydawca: Institute of Mathematical Statistics
DOI: 10.1214/21-ejs1933

A Compound Poisson Perspective of Ewens–Pitman Sampling Model

Autorzy: Emanuele Dolera, Stefano Favaro
Opublikowane w: Mathematics, 2021, ISSN 2227-7390
Wydawca: MDPI
DOI: 10.3390/math9212820

On consistent and rate optimal estimation of the missing mass

Autorzy: Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro
Opublikowane w: Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, Numer 57/3, 2021, Strona(/y) 1476-1494, ISSN 0246-0203
Wydawca: Elsevier BV
DOI: 10.1214/20-aihp1126

A Good-Turing estimator for feature allocation models

Autorzy: Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro
Opublikowane w: Electronic Journal of Statistics, Numer 13/2, 2019, Strona(/y) 3775-3804, ISSN 1935-7524
Wydawca: Institute of Mathematical Statistics
DOI: 10.1214/19-ejs1614

Nonparametric Bayesian multiarmed bandits for single-cell experiment design

Autorzy: Federico Camerlenghi, Bianca Dumitrascu, Federico Ferrari, Barbara E. Engelhardt, Stefano Favaro
Opublikowane w: The Annals of Applied Statistics, Numer 14/4, 2020, Strona(/y) 2003-2019, ISSN 1932-6157
Wydawca: Institute of Mathematical Statistics
DOI: 10.1214/20-aoas1370

A Common Atom Model for the Bayesian Nonparametric Analysis of Nested Data

Autorzy: Denti, Francesco; Camerlenghi, Federico; Guindani, Michele; Mira, Antonietta
Opublikowane w: Journal of the American Statistical Association, Numer 1, 2021, ISSN 1537-274X
Wydawca: Taylor and Francis
DOI: 10.6084/m9.figshare.14666073.v1

An information theoretic approach to post randomization methods under differential privacy

Autorzy: Fadhel Ayed, Marco Battiston, Federico Camerlenghi
Opublikowane w: Statistics and Computing, 2020, ISSN 0960-3174
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s11222-020-09949-3

Deep stable neural networks: Large-width asymptotics and convergence rates

Autorzy: Stefano Favaro; Sandra Fortini; Stefano Peluchetti
Opublikowane w: Bernoulli, 2023, ISSN 1350-7265
Wydawca: Chapman & Hall
DOI: 10.3150/22-bej1553

Rates of convergence in de Finetti’s representation theorem, and Hausdorff moment problem

Autorzy: Emanuele Dolera, Stefano Favaro
Opublikowane w: Bernoulli, Numer 26/2, 2020, Strona(/y) 1294-1322, ISSN 1350-7265
Wydawca: Chapman & Hall
DOI: 10.3150/19-bej1156

Doubly infinite residual neural networks: a diffusion process approach

Autorzy: Stefano Peluchetti, Stefano Favaro
Opublikowane w: Journal of Machine Learning Research, Numer 22, 2021, Strona(/y) 1-48, ISSN 1533-7928
Wydawca: MIT Press

Bayesian mixed effects models for zero-inflated compositions in microbiome data analysis

Autorzy: Boyu Ren, Sergio Bacallado, Stefano Favaro, Tommi Vatanen, Curtis Huttenhower, Lorenzo Trippa
Opublikowane w: The Annals of Applied Statistics, Numer 14/1, 2020, Strona(/y) 494-517, ISSN 1932-6157
Wydawca: Institute of Mathematical Statistics
DOI: 10.1214/19-aoas1295

Asymptotic Efficiency of Point Estimators in Bayesian Predictive Inference

Autorzy: Emanuele Dolera
Opublikowane w: Mathematics, Numer 4, 2022, ISSN 2227-7390
Wydawca: MDPI
DOI: 10.3390/math10071136

Consistent estimation of small masses in feature sampling

Autorzy: Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro
Opublikowane w: Journal of Machine Learning Research, Numer 22, 2021, ISSN 1533-7928
Wydawca: MIT press

Approximating Predictive Probabilities of Gibbs-Type Priors

Autorzy: Julyan Arbel, Stefano Favaro
Opublikowane w: Sankhya A, 2020, ISSN 0976-836X
Wydawca: Indian Statistical Institute
DOI: 10.1007/s13171-019-00187-y

Optimal disclosure risk assessment

Autorzy: Federico Camerlenghi, Stefano Favaro, Zacharie Naulet, Francesca Panero
Opublikowane w: The Annals of Statistics, 2020, ISSN 0090-5364
Wydawca: Institute of Mathematical Statistics

On uniform continuity of posterior distributions

Autorzy: Emanuele Dolera, Edoardo Mainini
Opublikowane w: Statistics & Probability Letters, Numer 157, 2020, Strona(/y) 108627, ISSN 0167-7152
Wydawca: Elsevier BV
DOI: 10.1016/j.spl.2019.108627

Scaled Process Priors for Bayesian Nonparametric Estimation of the Unseen Genetic Variation

Autorzy: Federico Camerlenghi; Stefano Favaro; Lorenzo Masoero; Tamara Broderick
Opublikowane w: Journal of the American Statistical Association, 2024, ISSN 0162-1459
Wydawca: American Statistical Association

Strong posterior contraction rates via Wasserstein dynamics

Autorzy: Dolera, Emanuele; Favaro, Stefano; Mainini, Edoardo
Opublikowane w: Probability Theory and Related Field, Numer 4, 2023, ISSN 0178-8051
Wydawca: Springer Verlag

More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics

Autorzy: Lorenzo Masoero, Federico Camerlenghi, Stefano Favaro, Tamara Broderick
Opublikowane w: Biometrika, 2021, ISSN 0006-3444
Wydawca: Oxford University Press
DOI: 10.1093/biomet/asab012

A Berry–Esseen theorem for Pitman’s $\alpha $-diversity

Autorzy: Emanuele Dolera, Stefano Favaro
Opublikowane w: Annals of Applied Probability, Numer 30/2, 2020, Strona(/y) 847-869, ISSN 1050-5164
Wydawca: Institute of Mathematical Statistics
DOI: 10.1214/19-aap1518

Perfect Sampling of the Posterior in the Hierarchical Pitman–Yor Process

Autorzy: Sergio Bacallado, Stefano Favaro, Samuel Power, Lorenzo Trippa
Opublikowane w: Bayesian Analysis, Numer -1/-1, 2021, ISSN 1936-0975
Wydawca: Carnegie Mellon University
DOI: 10.1214/21-ba1269

A Bayesian nonparametric approach to count-min sketch under power-law data streams

Autorzy: Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
Opublikowane w: Proceedings of the Twenty Fourth International Conference on Artificial Intelligence and Statistics, Numer 130, 2021, Strona(/y) 226-234, ISSN 2640-3498
Wydawca: MIT Press

Infinitely deep neural networks as diffusion processes

Autorzy: Stefano Peluchetti, Stefano Favaro
Opublikowane w: Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, Numer 108, 2020, Strona(/y) 1126-1136
Wydawca: MIT Press

Stable behaviour of infinitely wide deep neural networks

Autorzy: Stefano Favaro, Sandra Fortini, Stefano Peluchetti
Opublikowane w: Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, Numer 108, 2020, Strona(/y) 1137-1146
Wydawca: MIT Press

Large-width functional asymptotics for deep Gaussian neural networks

Autorzy: Daniele Bracale, Stefano Favaro, Sandra Fortini, Stefano Peluchetti
Opublikowane w: International Conference on Learning Representations, Numer 9, 2021, Strona(/y) 1-10
Wydawca: OpenReview

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