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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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Fwd: Postdoc jobs
by Matteo Ruggiero 05 Dec '22

05 Dec '22

ricevo e inoltro --- Matteo Ruggiero University of Torino and Collegio Carlo Alberto www.matteoruggiero.it > Inizio messaggio inoltrato: > > Da: Andreas Kyprianou <ak257(a)bath.ac.uk> > Oggetto: Postdoc jobs > Data: 5 dicembre 2022 08:42:23 CET > > A number of postdoc openings, please distribute to any potential candidates: > > https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5062452&ownertype=fair… <https://www.google.com/url?q=https://atsv7.wcn.co.uk/search_engine/jobs.cgi…> > > (To help explain the context: I am moving to Warwick from 1st Jan). > > Queries to Andreas Kyprianou (a.e.kyprianou(a)gmail.com <mailto:a.e.kyprianou@gmail.com>)

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post-doc grant at UNIFI
by Maria Elvira Mancino 03 Dec '22

03 Dec '22

Title: Non Gaussian multivariate time series models with applications to economics and finance. Deadline: 9/1/2023 link: https://bandi.miur.it/bandi.php/public/fellowship/id_fellow/224520 -- Maria Elvira Mancino, PhD Professor of Mathematical Finance Head of the Department of Economics and Management University of Firenze Via delle Pandette, 9 50127 Firenze https://www.unifi.it/p-doc2-2014-0-A-2b333931392b-1.html

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Thematic semester 2023 at Centre Henri Lebesgue
by Alessandra OCCELLI 01 Dec '22

01 Dec '22

Dear Colleagues, The Centre Henri Lebesgue is organising a thematic semester in probability that will take place in the summer semester 2023 between Angers, Nantes, Rennes and Roscoff. The semester consists in a series of conferences and summer schools on various topics, such as * Reflected Brownian motion: [ https://www.lebesgue.fr/en/40yearsRBM | https://www.lebesgue.fr/en/40yearsRBM ] * Probability and dynamics: [ https://www.lebesgue.fr/en/prody | https://www.lebesgue.fr/en/prody ] * Branching processes: [ https://www.lebesgue.fr/en/BPAA | https://www.lebesgue.fr/en/BPAA ] * Polymers and self-avoiding walks: [ https://www.lebesgue.fr/en/polywalks | https://www.lebesgue.fr/en/polywalks ] * Random nodal domains: [ https://www.lebesgue.fr/en/nodaldomain | https://www.lebesgue.fr/en/nodaldomain ] * Mean field models: [ https://www.lebesgue.fr/en/meanfield | https://www.lebesgue.fr/en/meanfield ] * Processes and heat kernels with symmetries: [ https://www.lebesgue.fr/en/heat | https://www.lebesgue.fr/en/heat ] The complete list of events can be found on the website [ https://www.lebesgue.fr/fr/ST2023 | https://www.lebesgue.fr/en/ST2023 ] . I would appreciate if you could circulate this announcement to those who may be interested. In particular, the CHL has allocated funds to cover accommodation and participation costs of some PhD students and young researchers. I hope many of you will join the West of France next year! Best regards, Alessandra Occelli

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