Items where Author is "Battiston, Marco"

Journal Article

Cabezas, Alberto and Battiston, Marco and Nemeth, Christopher (2024) Robust Bayesian nonparametric variable selection for linear regression. Stat, 13 (2): e696. ISSN 2049-1573

Ayed, Fadhel and Battiston, Marco and Camerlenghi, Federico and Favaro, Stefano (2021) On consistent and rate optimal estimation of the missing mass. Annales de l'institut Henri Poincare (B) Probability and Statistics, 57 (3). pp. 1476-1494. ISSN 0246-0203

Battiston, Marco and Ayed, Fadhel and Camerlenghi, Federico and Favaro, Stefano (2021) Consistent estimation of small masses in feature sampling. Journal of Machine Learning Research, 22 (6). pp. 1-28. ISSN 1532-4435

Ayed, Fadhel and Battiston, Marco and Camerlenghi, Federico (2020) An Information Theoretic approach to Post Randomization Methods under Differential Privacy. Statistics and Computing, 30. 1347–1361. ISSN 0960-3174

Ayed, Fadhel and Battiston, Marco and Camerlenghi, Federico and Favaro, Stefano (2019) A Good-Turing estimator for feature allocation models. Electronic Journal of Statistics, 13 (2). pp. 3775-3804. ISSN 1935-7524

Battiston, Marco and Favaro, Stefano and Teh, Yee Whye (2018) Multi-armed bandit for species discovery : A Bayesian nonparametric approach. Journal of the American Statistical Association, 113 (521). pp. 455-466. ISSN 0162-1459

Battiston, Marco and Favaro, Stefano and Roy, Daniel M. and Teh, Yee Whye (2018) A characterization of product-form exchangeable feature probability functions. Annals of Applied Probability, 28 (3). pp. 1423-1448. ISSN 1050-5164

Bacallado, S. and Battiston, Marco and Favaro, Stefano and Trippa, L. (2017) Sufficientness postulates for Gibbs-type priors and hierarchial generalizations. Statistical Science, 32 (4). pp. 487-500. ISSN 0883-4237

Contribution in Book/Report/Proceedings

Battiston, Marco and Ayed, Fadhel and Di Benedetto, Giuseppe (2020) A Bayesian Nonparametric Approach to Differentially Private Data. In: Privacy in Statistical Databases : UNESCO Chair in Data Privacy, International Conference, PSD 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer, ESP, pp. 32-48. ISBN 9783030575205

Monograph

Cabezas, Alberto and Battiston, Marco and Nemeth, Christopher (2021) Robust Bayesian Nonparametric Variable Selection for Linear Regression. Other. UNSPECIFIED.

Thesis

Cabezas Gonzalez, Alberto and Nemeth, Christopher and Battiston, Marco (2025) Advances in Bayesian Computation: Bridging Modern Machine Learning and Traditional Monte Carlo Methods. PhD thesis, Lancaster University.