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Seminar in Statistics - MARTA CATALANO
by Pierpaolo De Blasi 12 Dec '22

12 Dec '22

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 16 Dicembre 2022, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: *Marta Catalano* (University of Warwick) Title: *Optimal transport to measure the impact of the prior in Bayesian nonparametrics* Abstract: The Dirichlet process has been pivotal to the development of Bayesian nonparametrics, allowing one to learn the law of the observations through closed-form expressions. Still, its learning mechanism is often too simplistic and many generalizations have been proposed to increase its flexibility, a popular one being the class of normalized completely random measures. Here we investigate a simple yet fundamental matter: will a different prior actually guarantee a different learning outcome? To this end, we develop a new framework for assessing the merging rate of opinions based on three leading pillars: i) the investigation of identifiability of completely random measures; ii) the measurement of their discrepancy through a novel optimal transport distance; iii) the establishment of general techniques to conduct posterior analyses, unravelling both finite-sample and asymptotic behaviour of the distance as the number of observations grows. Our findings provide neat and interpretable insights on the impact of popular Bayesian nonparametric priors, with very mild assumptions on the data-generating process. ------------------------------------------------ Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/84498069342?pwd=ZkJOcnlNalEybmlEdE1QUGFEczZmdz09> Il seminario è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats -- Pierpaolo De Blasi University of Torino & Collegio Carlo Alberto carloalberto.org/pdeblasi <https://sites.google.com/a/carloalberto.org/pdeblasi/>

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PhD positions at the Maxwell Institute, Edinburgh
by Ottobre, Michela 09 Dec '22

09 Dec '22

Dear all, Heriot Watt and the Maxwell Institute, Edinburgh, are advertising a number of fully funded PhD Scholarships, of the duration of 3 and a half years. Applications are open in any area of Pure and Applied Mathematics, including (but not restricted to) Algebra, Mathematical Physics, Analysis of PDEs, Inverse Problems, Uncertainty Quantification, Calculus of Variations, Probability, Stochastic Analysis, Numerical Analysis, Mathematical Biology and Ecology, Modelling, Statistics, Computational Science, Actuarial Mathematics etc. The deadline for applications is 23rd of January 2023. We will accept applications also after this deadline, but best chances are before January 23rd. For information on our programmes, see the link below https://www.maxwell.ac.uk/graduate-school/ A description of (many of) the PhD projects offered by the HW research groups can be found here https://www.hw.ac.uk/uk/schools/mathematical-computer-sciences/research/phd… We actively promote Equality, Diversity and Inclusion and welcome applications from all qualified applicants. All the Best, Michela -------------------------------------- Michela Ottobre Associate Professor in Mathematics Heriot-Watt University ________________________________ Founded in 1821, Heriot-Watt is a leader in ideas and solutions. With campuses and students across the entire globe we span the world, delivering innovation and educational excellence in business, engineering, design and the physical, social and life sciences. This email is generated from the Heriot-Watt University Group, which includes: 1. Heriot-Watt University, a Scottish charity registered under number SC000278 2. Heriot- Watt Services Limited (Oriam), Scotland's national performance centre for sport. Heriot-Watt Services Limited is a private limited company registered is Scotland with registered number SC271030 and registered office at Research & Enterprise Services Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS. The contents (including any attachments) are confidential. If you are not the intended recipient of this e-mail, any disclosure, copying, distribution or use of its contents is strictly prohibited, and you should please notify the sender immediately and then delete it (including any attachments) from your system.

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postdoctoral position at Warwick
by Giuseppe Cannizzaro 09 Dec '22

09 Dec '22

Gentili colleghi, vi scrivo per comunicarvi che ho aperto una posizione di postdoc presso l'università Warwick per lavorare con me su argomenti di probabilità, analisi stocastica e meccanica statistica. https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5062452&ownertype=fair… Vi prego di incoraggiare buoni candidati che stanno completando o hanno completato il dottorato a fare domanda. Cari saluti, Giuseppe

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Fw: job announcement 6-year position in Econometrics/Statistics at TU Wien
by Avalos Pacheco, Alejandra 08 Dec '22

08 Dec '22

Buongiorno, ricevo ed inoltro. Alejandra Avalos-Pacheco, PhD ________________________________ From: Ulrike Schneider <ulrike.schneider(a)tuwien.ac.at> Sent: 01 December 2022 09:52 Subject: job announcement 6-year position in Econometrics/Statistics at TU Wien Dear colleagues, the Econometrics group at TU Wien is announcing a job opening for a 6-year assistant professor position (non-tenure track) in Econometrics/Statistics with earliest start date in March 2023. I would be grateful if you could forward the announcement to potentially interested candidates - thank you! Best wishes from Vienna, Ulrike

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Assistant Professor in Mathematics at Dublin City University
by Paolo Guasoni 08 Dec '22

08 Dec '22

The School of Mathematical Sciences in Dublin City University is inviting applications for the post of Assistant Professor in Mathematics. This is a permanent position, involving teaching and research. It is expected that the successful candidate will start in September 2023. Further details are at https://www.dcu.ie/sites/default/files/inline-files/BC221106%20Assistant%20… and the application form at https://www.dcu.ie/hr/vacancies-current-vacancies-external-applicants The closing date for applications being* Friday 6 January 2023*. Please bring this position to the attention of any interested candidates. -- * *Séanadh Ríomhphoist/Email Disclaimer* *Tá an ríomhphost seo agus aon chomhad a sheoltar leis faoi rún agus is lena úsáid ag an seolaí agus sin amháin é. Is féidir tuilleadh a léamh anseo. <https://sites.google.com/view/seanadh-riomhphoist>* *This e-mail and any files transmitted with it are confidential and are intended solely for use by the addressee. Read more here. <https://sites.google.com/view/dcu-email-disclaimer>* * -- <https://www.facebook.com/DCU/> <https://twitter.com/DCU> <https://www.linkedin.com/company/dublin-city-university> <https://www.instagram.com/dublincityuniversity/?hl=en> <https://www.youtube.com/user/DublinCityUniversity>

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(PMS)^2 talk - Mario Maurelli - December 13 at 17.30
by Margherita Zanella 07 Dec '22

07 Dec '22

Dear colleagues, We are happy to announce the following online talk: Speaker: Mario Maurelli(Università di Pisa). Title: A McKean-Vlasov SDE and particle system with interaction from reflecting boundaries. Abstract: We consider a one-dimensional McKean-Vlasov SDE on a domain and the associated meanfield interacting particle system. The peculiarity of this system is the combination of the interaction, which keeps the average position prescribed, and the reflection at the boundaries; these two factors make the effect of reflection non local. We show path-wise well-posedness for the McKean-Vlasov SDE and convergence for the particle system in the limit of large particle number. Joint work with Michele Coghi, Wolfgang Dreyer, Peter K. Friz, Paul Gajewski, Clemens Guhlke. Date and time: Tuesday December 13, 17:30-18:30 (Rome time zone) Link: Entra nella riunione in Zoom https://polimi-it.zoom.us/j/92900386273?pwd=dG1xTUtsN0JpaFl2TWlzRTJ1a0lBZz09 ID riunione: 929 0038 6273 Passcode: 638099 This talk is part of the (PMS)^2: Pavia-Milano Seminar series on Probability and Mathematical Statistics organized jointly by the universities Milano-Bicocca, Pavia, Milano-Politecnico. Participation is free and welcome! Best regards The organizers (Carlo Orrieri, Maurizia Rossi, Margherita Zanella)

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Seminario del Dott. Ascari - 14 dicembre 16.00
by Enea Bongiorno 07 Dec '22

07 Dec '22

Buongiorno, con piacere segnalo il seguente seminario: -------------------------------- 14 dicembre ore 16.00 - aula 203, campus Perrone, via Perrone, 18, Novara. Università del Piemonte Orientale. - on-line: meet.google.com/yvq-ccbt-pzt Dott. Roberto Ascari Università di Milano-Bicocca Title: The flexible Latent Dirichlet Allocation Abstract: Over recent years, text modeling techniques have been employed in several applications, including the detection of latent topics in text documents. A widespread statistical tool for topic modeling is the Latent Dirichlet Allocation (LDA), which allows for a document representation in terms of topic composition. A well-known limitation of the LDA is related to the stiffness of the Dirichlet prior imposed on the topic distributions. To consider a richer dependence structure, we propose a generalization of the Dirichlet distribution as an alternative distribution, namely the flexible Dirichlet (FD). The FD is a distribution defined on the simplex space allowing for a finite mixture structure. This choice introduces additional parameters in the LDA, and ensures more flexibility, still maintaining the model interpretability, as well as conjugacy to the multinomial model. The latter property allows for a Collapsed Gibbs Sampling-based estimation procedure. The generalization of the LDA based on the FD distribution is illustrated via an application to a real dataset. ----------------------------------- Tutti gli interessati sono invitati a partecipare. Cordiali saluti, Enea -- Enea Bongiorno,PhD Associate Professor of Statistics Università degli Studi del Piemonte Orientale Via Perrone 18, 28100, Novara, Italia Phone: +390321375317 enea.bongiorno(a)uniupo.it upobook.uniupo.it/enea.bongiorno

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SPASS seminar: Milo Viviani - TUE 13.12 at 14:00
by Andrea Agazzi 07 Dec '22

07 Dec '22

Dear Colleagues, We would like to invite you to the following SPASS <https://sites.google.com/unipi.it/spass> seminar, jointly organized by UniPi, SNS, UniFi and UniSi: *On the infinite dimension limit of invariant measures and solutions of Zeitlin's 2D Euler equations* by Milo Viviani (Centro de Giorgi, Scuola Normale Superiore di Pisa) The seminar will take place in person on *TUE, 13.12.2022 at 14:00 CET* in Aula Seminari, Department of Mathematics, University of Pisa and streamed online here <https://meet.google.com/gji-phwo-vbg>. The organizers, A. Agazzi, G. Bet, A. Caraceni, F. Grotto, G. Zanco https://sites.google.com/unipi.it/spass -------------------------------------------- *Title: **On the infinite dimension limit of invariant measures and solutions of Zeitlin's 2D Euler equations* *Abstract: **In this talk we consider a finite dimensional approximation for the 2D Euler equations on the sphere, proposed by V. Zeitlin, and show their convergence towards a solution of the Euler equations with marginals distributed as the enstrophy measure. The method relies on nontrivial computations on the structure constants of the Poisson algebra of functions on S², that appear to be new. Finally, we discuss the problem of extending our results to Gibbsian measures associated with higher Casimirs, via Zeitlin’s model.*

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Seminar Wager @Bocconi - 12Dec at 12:00
by Giacomo Zanella 06 Dec '22

06 Dec '22

We are glad to announce the following hybrid seminar: Monday, 12 of December 2022 at 12:00 In person: Room 3-E4-SR03, floor 3, Bocconi University, Via Roentgen 1, Milan Zoom link: https://unibocconi-it.zoom.us/j/95882011831; Meeting ID: 958 8201 1831 Speaker: Stefan Wager (Stanford University) Title: Learning from a Biased Sample Abstract: The empirical risk minimization approach to data-driven decision making assumes that we can learn a decision rule from training data drawn under the same conditions as the ones we want to deploy it under. However, in a number of settings, we may be concerned that our training sample is biased, and that some groups (characterized by either observable or unobservable attributes) may be under- or over-represented relative to the general population; and in this setting empirical risk minimization over the training set may fail to yield rules that perform well at deployment. Building on concepts from distributionally robust optimization and sensitivity analysis, we propose a method for learning a decision rule that minimizes the worst-case risk incurred under a family of test distributions whose conditional distributions of outcomes Y given covariates X differ from the conditional training distribution by at most a constant factor, and whose covariate distributions are absolutely continuous with respect to the covariate distribution of the training data. We apply a result of Rockafellar and Uryasev to show that this problem is equivalent to an augmented convex risk minimization problem. We give statistical guarantees for learning a robust model using the method of sieves and propose a deep learning algorithm whose loss function captures our robustness target. We empirically validate our proposed method in simulations and a case study with the MIMIC-III dataset. Best regards, Giacomo Zanella

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Corso Marta CATALANO (University of Warwick)
by Matteo Ruggiero 05 Dec '22

05 Dec '22

Cari colleghi, nell’ambito del programma di Visiting Professors della Laurea Magistrale in Stochastics and Data Science dell’Università di Torino (il programma completo è consultabile alla pagina https://www.master-sds.unito.it/go/visiting), con piacere annunciamo il seguente corso: -------------------------------------- MARTA CATALANO (University of Warwick) DEPENDENT NONPARAMETRIC PRIORS VIA COMPLETELY RANDOM MEASURES Bayesian nonparametrics provides a natural framework for performing flexible inference with principled quantification of uncertainty. The main ingredients are discrete random measures, whose laws act as prior distribution for infinite-dimensional parameters and, combined with the data, provide their posterior distribution. Recent works use dependent random measures to perform simultaneous inference across multiple samples. The borrowing of strength across different samples is regulated by the dependence structure of the random measures, with complete dependence corresponding to maximal sharing of information and fully exchangeable observations. In these lectures we start from the notion of completely random measure and describe several ways of introducing dependence between them. Different models may still induce the same amount of borrowing of information, measured by an index of dependence. In the two sample case, this is often achieved by second order summaries of the joint distribution through linear correlation. In the multivariate scenario, we characterise dependence in terms of distance from exchangeability by relying on optimal transport. This allows for informed prior elicitations and provides a fair ground for model comparison. -------------------------------------- Il corso si svolgerà solo in presenza secondo il seguente calendario Lez 1: mar 13/12: 14-16 - Aula 4 Lez 2: mer 14/12: 9.15-11.15 - Aula 4 Lez 3: mer 14/12: 14-16 - Aula 30 Lez 4: gio 15/12: 14-16 - Aula 11 Sede dei corsi: Corso Unione Sovietica 218/bis, 10134, Torino Il corso è rivolto agli studenti della Laurea Magistrale ma la partecipazione è aperta a tutti gli interessati. Cordiali saluti, Matteo Ruggiero --- Matteo Ruggiero University of Torino and Collegio Carlo Alberto www.matteoruggiero.it

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