Stefano Favaro
Professor of Statistics, Università
di Torino
Departimento di Scienze Economico-Sociali e Matematico-Statistiche
Università di Torino
Corso Unione Sovietica 218/bis
10134 Torino, Italy
Telephone: +39 011 6705724
Email: stefano(.)favaro(at)unito(.)it
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Research interests: nonparametric Bayes and empirical Bayes methods,
statistical machine learning, data confidentiality and fairness,
learning-augmented recovery algorithms, mathematics of deep learning
My research is supported by a European Research Council (ERC)
consolidator grant (2019 - 2024)
Papers:
[1] Main
publications
- Learning-augmented count-min sketches via Bayesian nonparametrics, with E. Dolera and S. Peluchetti
- Journal
of Machine Learning Research,
to appear
- [DOI]
[PDF]
- Bayesian nonparametric mixture modeling for temporal dynamics of gender stereotypes, with M. De Iorio, A. Guglielmi and Y. Lifeng
- Annals of Applied Statistics,
to appear
- [DOI]
[PDF]
- Deep Stable neural networks: large-width asymptotics and convergence rates, with S. Fortini and S. Peluchetti
- Bernoulli,
to appear
- [DOI]
[PDF]
- Near-optimal estimation of the unseen under regularly varying tail populations, with Z. Naulet
- Bernoulli,
to appear
- [DOI]
[PDF]
- Scaled process priors for Bayesian nonparametric estimation of the unseen genetic variation, with T. Broderick, F. Camerlenghi and L. Masoero
- Journal
of the American Statistical Association,
to appear
- [DOI]
[PDF]
- Conformalized frequency estimation from sketched data, with M. Sesia
- Advances in Neural Information Processing Systems,
2022
- [NeurIPS]
- Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions, with A. Bordino and S. Fortini
- Transactions on Machine Learning Research, 2022
- [DOI]
[PDF]
- More for less: predicting and
maximizing genetic variant discovery via Bayesian nonparametrics, with
T. Broderick, F. Camerlenghi and L. Masoero
- Biometrika,
2022, vol. 109, pp. 17-32
- [DOI]
[PDF]
- Bayesian nonparametric disclosure risk assessment, with F. Panero and T. Rigon
- Electronic Journal of Statistics,
2021, vol. 15, pp. 5626-5651
- [DOI]
[PDF]
- Consistent and rate optimal estimation
of the missing mass, with F. Ayed, M. Battiston and F. Camerlenghi
- Annales
de l'Institut Henri Poincaré - Probabilités et Statistiques,
2021, vol. 57, pp. 1476-1494
- [DOI]
[PDF]
- Doubly infinite neural networks: a
diffusion process approach, with S. Peluchetti
- Journal
of Machine Learning Research,
2021, vol. 22, pp. 1-48
- [DOI]
[PDF]
- Large-width functional asymptotics for
deep Gaussian neural networks, with D. Bracale, S. Fortini and S.
Peluchetti
- International
Conference on Learning Representations, 2021
- [ICLR]
- A Bayesian nonparametric approach to
count-min sketch under power-law data streams, with E. Dolera and S.
Peluchetti
- International
Conference on Artificial Intelligence and Statistics,
2021
- [AISTATS]
- Optimal disclosure risk assessment,
with F. Camerlenghi, Z. Naulet and F. Panero
- Annals
of Statistics, 2021,
vol. 49, pp. 723-744
- [DOI]
[PDF]
- Perfect sampling for posterior
hierarchical Pitman-Yor processes, with S. Bacallado and L. Trippa
- Bayesian
Analysis, 2021, vol. 17, pp. 685-709
- [DOI]
[PDF]
- Consistent estimation of small masses
in feature sampling, with F. Ayed, M. Battiston and F. Camerlenghi
- Journal
of Machine Learning Research,
2021, vol. 22, pp. 1-28
- [DOI]
[PDF]
- Stable behaviour of infinitely wide
deep neural networks, with S. Fortini and S. Peluchetti
- International
Conference on Artificial Intelligence and Statistics, 2020
- [AISTATS]
- Infinitely deep neural networks as
diffusion processes, with S. Peluchetti
- International
Conference on Artificial Intelligence and Statistics, 2020
- [AISTATS]
- Nonparametric Bayesian multi-armed
bandits for single cell experiment design, with F. Camerlenghi, B.
Dimitrascu, B. Engelhardt and F. Ferrari
- Annals
of Applied Statistics,
2020, vol. 14, pp. 2003-2019
- [DOI]
[PDF]
- Rates of convergence in de Finetti's
representation theorem, and Hausdorff moment problem, with E. Dolera
- Bernoulli,
2020, vol. 26, pp. 1294-1322
- [DOI]
[PDF]
- A Berry-Esseen theorem for Pitman's
alpha-diversity, with E. Dolera
- Annals
of Applied Probability,
2020, vol. 30, pp. 847-869
- [DOI]
[PDF]
- Approximating predictive probabilities
of Gibbs-type priors, with J. Arbel
- Sankhya
Series A, 2020, vol. 83, pp. 496-519
- [DOI]
- Bayesian mixed effects models for
zero-inflated compositions in microbiome data analysis, with S.
Bacallado, C. Huttenhower, B. Ren and L. Trippa
- Annals
of Applied Statistics, 2020, vol. 14, pp. 494-517
- [DOI]
[PDF]
- A Good-Turing estimator for feature
allocation models, with F. Ayed, M. Battiston and F. Camerlenghi
- Electronic
Journal of Statistics, 2019, vol. 13, pp. 3775-3804
- [DOI] [PDF]
- Bayesian nonparametric analysis of
Kingman's coalescent, with S. Feng and P. Jenkins
- Annales
de l'Institut Henri Poincaré - Probabilités et Statistiques,
2019, vol. 55, pp. 1087-1115
- [DOI]
[PDF]
- Modeling population structure under
hierarchical Dirichlet processes, with K. Adhikari, M. De Iorio, L.
Elliott and Y.W. Teh
-
Bayesian Analysis, 2019, vol. 14, pp. 313-339
- [DOI]
- Multi-armed bandits for species
discovery: a Bayesian nonparametric approach, with M. Battiston and Y.W.
Teh
- Journal
of the American Statistical Association, 2018, vol. 113, pp.
455-466
- [DOI]
- Dependent generalized Dirichlet priors
for the analysis of acute lymphoblastic leukaemia, with W. Barcella, M.
De Iorio and G. Rosner
- Biostatistics,
2018, vol. 19, pp. 342-358
- [DOI]
- Moderate deviations for Ewens-Pitman
sampling models, with S. Feng and F. Gao
- Sankhya
Series A, 2018, vol. 80, pp. 330-341
- [DOI]
- A characterization of product-form
exchangeable feature probability functions, with M. Battiston, D.M. Roy
and Y.W. Teh
- Annals
of Applied Probability,
2018, vol. 28, pp. 1423-1448
- [DOI]
[PDF]
- Posterior representations of
hierarchical completely random measures in trait allocation models, with
T. Broderick, F. Camerlenghi and L. Masoero
- Advances
in Neural Information Processing Systems, 2018
- [NeurIPS]
- On a general Maclaurin's inequality,
with S.G. Walker
- Proceedings
of the American Mathematical Society, 2018, vol. 146, pp.
175-188
- [DOI]
- "Sufficientness" postulates for
Gibbs-type priors and hierarchial generalizations, with S. Bacallado, M.
Battiston and L. Trippa
- Statistical
Science, 2017, vol. 32, pp. 487-500
- [DOI]
[PDF]
- A marginal sampler for sigma-stable Poisson-Kingman mixture models,
with M. Lomeli and Y.W. Teh
- Journal
of Computational and Graphical Statistics, 2017, vol. 26, pp.
44-53
- [DOI]
- Bayesian nonparametric ordination for
the analysis of microbial communities, with S. Bacallado, S. Holmes, B.
Ren and L. Trippa
- Journal
of the American Statistical Association, 2017, vol. 112, pp.
1430-1442
- [DOI]
- Bayesian nonparametric inference for
discovery probabilities: credible intervals and large sample
asymptotics, with J. Arbel, B. Nipoti and Y.W. Teh
- Statistica
Sinica, 2017, vol. 27, pp. 839-858
- [DOI]
- Rediscovery of Good-Turing estimators
via Bayesian nonparametrics, with B. Nipoti and Y.W. Teh
- Biometrics,
2016, vol. 72, pp. 136-145
- [DOI]
- Frequency of frequencies distributions
and size-dependent exchangeable random partitions, with S.G. Walker and
M. Zhou
- Journal
of the American Statistical Association, 2016, vol. 112, pp.
1623-1635
- [DOI]
- On the stick-breaking representation
for homogeneous NRMIs, with A. Lijoi, B. Nipoti, I. Pruenster and Y.W.
Teh
- Bayesian Analysis, 2016, vol.
11, pp. 697-724
- [DOI]
[PDF]
- A note on nonparametric inference for
species variety with Gibbs-type priors, with L.F. James
- Electronic Journal of Statistics, 2015,
vol. 9, pp. 2884-2902
- [DOI]
[PDF]
- Relatives of the Ewens sampling formula
in Bayesian nonparametrics, with L.F. James
- Statistical
Science, 2016, vol. 31, pp. 30-33
- [DOI]
- Random variate generation for
Laguerre-type exponentially tilted alpha-stable distributions, with B.
Nipoti and Y.W. Teh
- Electronic Journal of Statistics, 2015,
vol. 9, pp. 1230-1242
- [DOI]
[PDF]
- Large deviation principles for the
Ewens-Pitman sampling model, with S. Feng
- Electronic
Journal of Probability, 2015,
vol. 20, pp. 1-27
- [DOI]
[PDF]
- Bayesian regularization of the length of memory in reversible
sequences, with S. Bacallado, L. Trippa
- Journal
of the Royal Statistical Society Series B, 2016, vol. 78, pp.
933-946
- [DOI]
- Looking-backward probabilities for Gibbs-type exchangeable random
partitions, with S. Bacallado and L. Trippa
- Bernoulli, 2015, vol. 21, pp.
1-37
- [DOI]
[PDF]
- A hybrid sampler for Poisson-Kingman
mixture models, with M. Lomeli and Y.W. Teh
- Advances
in Neural Information Processing Systems, 2015
- [NeurIPS]
- On the stick-breaking representation of
sigma-stable Poisson-Kingman models, with M. Lomeli, B. Nipoti and Y.W.
Teh
- Electronic Journal of Statistics,
2014, vol. 8, pp. 1063-1085
- [DOI]
[PDF]
- Bayesian nonparametric analysis of reversible Markov chains, with S.
Bacallado and L. Trippa
- Annals of Statistics, 2013, vol.
41, pp. 870-896
- [DOI]
[PDF]
- Posterior analysis of rare variants in
Gibbs-type species sampling models, with O. Cesari and B. Nipoti
- Journal of Multivariate Analysis,
2014, vol. 131, pp. 79-98
- [DOI]
- Asymptotics for the number of blocks in
a conditional Ewens-Pitman sampling model, with S. Feng
- Electronic Journal of Probability,
2014, vol. 19, pp. 1-15
- [DOI]
[PDF]
- MCMC for normalized random measure mixture models, with Y.W. Teh
- Statistical Science, 2013, vol.
28, pp. 335-359
- [DOI]
[PDF]
- A new estimator of the discovery probability, with A. Lijoi and I.
Pruenster
- Biometrics, 2012, vol. 68. pp.
1188-1196
- [DOI]
- Conditional formulae for Gibbs-type exchangeable random partitions,
with A. Lijoi and I. Pruenster
- Annals of Applied Probability,
2013, vol. 23, pp. 1721-1754
- [DOI]
[PDF]
- On the stick-breaking representation of normalized inverse Gaussian
priors, with A. Lijoi and I. Pruenster
- Biometrika, 2012, vol. 99, pp.
663-674
- [DOI]
- Slice sampling sigma-stable Poisson-Kingman mixture models, with S.G.
Walker
- Journal of Computational and
Graphical Statistics, 2013, vol. 22, pp. 830-847
- [DOI]
- Alpha-diversity processes and normalized inverse Gaussian diffusions,
with M. Ruggiero and S.G. Walker
- Annals of Applied Probability,
2013, vol. 23, pp. 386-425
- [DOI]
[PDF]
- Asymptotics for a Bayesian nonparametric estimator of species
richness, with A. Lijoi and I. Pruenster
- Bernoulli, 2012, vol. 18, pp.
1267-1283
- [DOI]
[PDF]
- A class of normalized random measure with an exact predictive sampling
scheme, with L. Trippa
- Scandinavian Journal of Statistics,
2012, vol. 39, pp. 444-460
- [DOI]
- A class of measure-valued Markov chains and Bayesian nonparametrics,
with A. Guglielmi and S.G. Walker
- Bernoulli, 2012, vol. 18, pp.
1002-1030
- [DOI]
[PDF]
- On a generalized Chu-Vandermonde identity, with I. Pruenster and S.G.
Walker
- Statistics and Probability Letters,
2012, vol. 14, pp. 253-262
- [DOI]
- On a class of distributions on the simplex, with G. Hadjicharalambous
and I. Pruenster
- Journal of Statistical Planning and
Inference, 2011, vol. 141, pp. 2987-3004
- [DOI]
- On a class of random probability measures with a general predictive
structure, with I. Pruenster and S.G. Walker
- Scandinavian Journal of Statistics,
2011, vol. 38, pp. 359-376
- [DOI]
- A class of neutral to the right priors induced by superposition of
beta processes, with P. De Blasi and P. Muliere
- Journal of Statistical Planning and
Inference, 2010, vol. 140, pp. 1563-1575
- [DOI]
- On the distribution of sums of exponential random variables via Wilk's
integral representation, with S.G. Walker
- Acta Applicandae Mathematicae,
2010, vol. 109, pp. 1035-1042
- [DOI]
- Bayesian nonparametric inference for
species variety with a two parameter Poisson-Dirichlet process prior,
with A. Lijoi, R.H. Mena and I. Pruenster
- Journal of the Royal Statistical
Society Series B, 2009, vol. 71 pp. 992-1008
- [DOI]
- A Gibbs-sampler based random process in Bayesian nonparametrics, with
M. Ruggiero and S.G. Walker
- Electronic Journal of Statistics,
2009, vol. 3, pp. 1557-1567
- [DOI]
[PDF]
- A generalized constructive definition for the Dirichlet process, with
S.G. Walker
- Statistics and Probability Letters,
2008, vol. 78, pp. 2836-2838
- [DOI]
[2] Conference
proceedings and other publications
- Infinite-channel deep Stable convolutional neural networks, with D. Bracale, S. Fortini and S. Peluchetti
- Workshop on "Bayesian Deep Learning" at NeurIPS, 2021
- [DOI]
- On Johnson's "sufficientness" postulates for feature sampling models, with F. Camerlenghi
- Mathematics - A festschrift for Eugenio Regazzini's 75th birthday -, to appear
- [DOI]
- A compound Poisson perspective of Ewens-Pitman sampling model, with E. Dolera
- Mathematics - A festschrift for Eugenio Regazzini's 75th birthday -, to appear
- [DOI]
- Upscaling human activity data: an
ecological perspective, with M. Formentin, A. Maritan, S. Stivanello, S.
Suweis and A. Tovo
- PLoS
ONE, to appear
- [DOI]
- Genomic variety prediction via Bayesian
nonparametrics, with T. Broderick, F. Camerlenghi and L. Masoero
- Symposium
on "Advances in Approximate Bayesian Inference", 2019
- [AABI]
- Neural SDE: information propagation
through the lens of diffusion processes, with S. Peluchetti
- Workshop
on "Bayesian Deep Learning" at NeurIPS, 2019
- [NeurIPS]
- Discussion of "Sparse graphs using
exchangeable random measures" by F. Caron and E.B. Fox, with M.
Battiston
- Journal
of the Royal Statistical Society Series B, 2017, vol. 79, pp.
1343-1344
- [DOI]
- Addendum to "On a general Maclaurin's
inequality" with S.G.Walker
- Proceedings
of the American Mathematical Society, 2018, vol. 146, pp.
2217-2218
- [DOI]
- Bayesian nonparametric inference for
shared species richness in multiple populations, with S. Bacallado and
L. Trippa
- Journal of Statistical Planning and
Inference - special issue on
Bayesian nonparametrics -, 2015, vol. 166, pp. 14-23
- [DOI]
- Bayesian inference on population
structure: from parametric to nonparametric modeling, with M. De Iorio
and Y.W. Teh
- Nonparametric
Bayesian Inference in Biostatistics, 2015, Springer
- [Springer]
- Are Gibbs-type priors the most natural generalization of the Dirichlet
process?, with P. De Blasi, A. Lijoi, R.H. Mena, I. Pruenster and M.
Ruggiero
- IEEE Transactions on Pattern
Analysis and Machine Intelligence -
special issue on Bayesian nonparametrics -, 2015, vol. 37, pp.
212-229
- [DOI]
- On a class of sigma-stable
Poisson-Kingman models and an effective marginalized sampler, with M.
Lomeli and Y.W. Teh
- Statistics
and Computing - special issue MCMSki IV -, 2015, vol. 25, pp.
67-78
- [DOI]
- Discussion of "On simulation and
properties of stable law" by L. Devroye and L.F. James, with B. Nipoti
- Statistical
Methods and Applications, 2014, vol. 23, pp. 365-369
- [DOI]
- Two tales about Bayesian nonparametric modeling, with P. De Blasi, A.
Lijoi, R.H. Mena and I. Pruenster
- Workshop on "Bayesian Statistical
Sciences" at JSM, 2012
- [JSM]
- Contributions to the Dirichlet process and related classes of random
probability measures
- Ph.D. Thesis, Dipartimento di
Scienze delle Decisioni, Università Commerciale "L. Bocconi", 2009
- [Università
"L. Bocconi"]
[3] Submitted
papers
- Reinforced urn processes indexed by the
vertices of a recombinant binary tree, with D. Ait Aoudia and P. Muliere
Submitted, 2010
- Bayesian nonparametric inference for "species-sampling" problems, with C. Balocchi and Z. Naulet
Submitted, 2022
- A Bayesian nonparametric approach to species sampling problems with ordering, with C. Balocchi and F. Camerlenghi
Submitted, 2022
- Strong posterior contraction
rates via Wasserstein dynamics, with E. Dolera and E. Mainini
Submitted, 2022
- Conformal frequency estimation with sketched data under relaxed exchangeability, with E. Dobriban and M. Sesia
Submitted, 2022
- Wasserstein posterior contraction rates in non-dominated Bayesian nonparametric models, with F. Camerlenghi, E. Dolera and E. Mainini
Submitted, 2022
- Bayesian nonparametric estimation of coverage probabilities and distinct counts from sketched data, with M. Sesia
- Submitted, 2022
- The power of private likelihood-ratio tests for goodness-of-fit in frequency tables, with E. Dolera
Submitted, 2022
- Large-width asymptotics for ReLU neural networks with alpha-Stable initializations, with S. Fortini and S. Peluchetti
Submitted, 2022
Editorial boards: I am Associate Editor of Bernoulli and Statistical Science
Some links: