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Seminar: Bayesian network structural learning from complex survey data - P. Vicard
by Mira Antonietta 15 May '24

15 May '24

On behalf of Prof Di Serio I am sharing the following announcement ———————- The Statistical Network Science committee of the Bernoulli Society invites you to an online talk this week Thursday: Thursday May 16 2-3 pm UK time Title: Bayesian network structural learning from complex survey data Statistical Network Science Seminar Series- Bernoulli Society Speaker: Paola Vicard (Department of Economics, Università Roma Tre, Rome, Italy) Abstract: The association structure of a Bayesian network can be known in advance by subject matter knowledge or have to be learned from a database. One of the most widely used procedures is the PC algorithm consisting in carrying out several independence tests on the available data set and in building a Bayesian network according to the tests results. In case of data driven learning, the PC algorithm is based on the irremissible assumption that data are independent and identically distributed. Unfortunately, official statistics data are generally collected through complex sampling designs, then the aforementioned assumption is not met. In such a context the PC algorithm fails in learning the structure. To avoid this, the sample selection must be taken into account in the structural learning process. A modified version of the PC algorithm is proposed for inferring causal structure from complex survey data. It is based on resampling techniques for finite populations. A simulation experiment showing the robustness with respect to departures from the assumptions and the good performance of the proposed algorithm is carried out. (Joint work with Daniela Marella, Sapienza Università di Roma) Zoom link https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fzoom.us%2…<https://zoom.us/j/99820613967> Meeting ID: 998 2061 3967 Passcode: 850644 All welcome Clelia Di Serio and Gesine Reinert

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avviso di seminario di A. Buonocore e L. Caputo
by Antonio DI CRESCENZO 14 May '24

14 May '24

scusandomi per invii multipli... ---------- Forwarded message --------- *UNIVERSITA' DI SALERNO* *Dipartimento di Matematica* AVVISO DI SEMINARIO *Speaker*: *Aniello* *BUONOCORE *e *Luigia* *CAPUTO* (Dipartimento di Matematica e Applicazioni, Università di Napoli Federico II) *Titolo*: *Il tema "Dati e Previsioni" presente nelle Indicazioni Nazionali e nelle Linee Guida è: un problema oppure una risorsa da valorizzare?* *Data*: mercoledì 15 maggio 2024, ore 11:30 *Luogo*: Sala Riunioni, Edificio F2, piano 1, stanza 36, e su Teams, al link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_ Yjc2NjU5ZDEtOTQ3YS00YzcyLTg3MTItNzRlMDg4YWU2Nzli%40thread. v2/0?context=%7b%22Tid%22%3a%22c30767db-3dda-4dd4-8a4d- 097d22cb99d3%22%2c%22Oid%22%3a%2261e4e421-60a6-4cb9-8153-d04cb91c1edf%22%7d *Abstract* Per il tema "Dati e Previsioni" si propone l'impostazione didattica basata sui problemi. In particolare, si propone di utilizzare, in maniera appropriata e con la finalità di sollecitare le abilità comunicative ed argomentative, alcuni problemi e paradossi della probabilità condizionata che nel corso del tempo sono stati occasione di discussioni vivaci e intriganti. I problemi selezionati e sperimentati nel corso degli ultimi anni in classi della scuola secondaria, nei quali l'enfasi è posta soprattutto sul significato dei simboli e delle formule, forniscono anche un modo per stimolare gli obiettivi di "processo" (argomentare e dimostrare, comunicare, rappresentare, collegare) spesso trascurati a favore dei soli obiettivi di "contenuto". Una tale modalità operativa può essere d'aiuto sia agli insegnanti per mitigare le difficoltà che loro stessi soventemente riscontrano nella concettualizzazione (ovvero quella discontinuità tra i processi cognitivi degli studenti e l'astrazione) e sia agli stessi studenti per meglio orientarsi quando le circostanze della vita quotidiana sicuramente lo richiederanno. Gli interessati sono cordialmente invitati a partecipare, *Antonio Di Crescenzo* *Barbara Martinucci* *Alessandra Meoli* *Serena Spina*

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SAVE THE DATE - Tavola rotonda su "Iperautorialità e riviste predatorie" - 29 maggio 2024 - ore 15
by ANDREA CONSIGLIO 14 May '24

14 May '24

Cari Colleghi, vi ricordiamo l’appuntamento per tavola rotonda su "Iperautorialità e Riviste Predatorie" L’evento è fissato per il 29 maggio alle ore 15:00 CET, presso l'Aula delle lauree della Facoltà di Economia. Potrete seguire la discussione online tramite una piattaforma telematica: https://uniroma1.zoom.us/j/84228305285 Per la partecipazione in presenza, si prega di registrarsi entro e non oltre il 20/05/2024 https://bit.ly/AMASES-TavolaRotonda Contiamo sulla vostra numerosa partecipazione. Cordiali saluti, Il Comitato Scientifico AMASES %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Tavola Rotonda: Iperautorialità e Riviste Predatorie Data e Luogo: 29 maggio 2024, ore 15.00, Aula delle lauree, Facoltà di Economia, via Castro Laurenziano 9, Roma. Saluti Istituzionali: Giovanni Di Bartolomeo, Preside Facoltà di Economia, Università di Roma "La Sapienza" Andrea Consiglio, Presidente AMASES, Università di Palermo Partecipanti: Santo Fortunato, Indiana University Giulia Iori, Università di Venezia "Cà Foscari" Marco Malgarini, ANVUR Angelo Pezzullo, Università Cattolica Angela Santoni, Commissione Etica, Università di Roma "La Sapienza" Francesco Sylos Labini, CREF Moderatore: Marco Li Calzi, Università di Venezia "Cà Foscari" Andrea Consiglio Università di Palermo Dipartimento di Scienze Economiche, Aziendali e Statistiche. Viale delle Scienze, Edificio 13 90128 Palermo, Italy tel:++39-09123895228 fax:++39-091485726 skype: conan_66 email:andrea.consiglio@unipa.it<mailto:email%3Aandrea.consiglio@unipa.it> pec:andrea.consiglio@pec.it<mailto:pec%3Aandrea.consiglio@pec.it> www:http://bit.ly/AndreaConsiglio

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PhD courses at Roma Tre University
by Francesco Cesarone 14 May '24

14 May '24

Dear All, I am happy to announce a new upcoming series of PhD courses organized by the Research Group on Quantitative Finance, Department of Business Studies – Roma Tre University. Below are some details on the different topics covered, speakers, and dates: * Introduction to Graph Theory and Applications Andrea Scozzari - Full Professor of Mathematical Methods of Economics, Finance and Actuarial Sciences at University Niccolò Cusano, Department of Economics. Date: Monday 20th May, h: 14:30 - 17:30; Wednesday 22nd May, h: 14:30 - 17:30; Friday 24th May, h: 14:30 - 17:30; Monday 27th May, h: 14:30 - 17:30. * AI Algorithms Valerio Giuseppe Sasso - Scholar in Operations Research at Sapienza University of Rome, Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG). Date: Wednesday 29th May, h: 14:30 - 17:30; Friday 31st May, h: 14:30 - 17:30; Monday 3rd June, h: 14:30 - 17:30; Wednesday 5th June, h: 14:30 - 17:30; Friday 7th June, h: 10:00 - 12:00/14:30 - 16:30. * Stochastic Dynamic Optimization Massimiliano Corradini, Researcher at Roma Tre University. Date: Monday 10th June, h: 11:00 - 14:00; Friday 14th June, h: 11:00 - 14:00; Monday 17th June, h: 11:00 - 14:00; Thursday 20th June, h: 11:00 - 14:00. The seminars can be attended either physically at the Computer lab (small room), ground floor (Department of Business Studies - Roma Tre University, Via Silvio D'Amico, 77, 00145 Rome, Italy) or online via teams. For more information I refer to the following web page<https://www.francescocesarone.com/phd/phd-courses>. Best regards, Francesco Cesarone F Cesarone (2020), Computational Finance. MATLAB oriented modeling, Routledge-Giappichelli Studies in Business and Management, ISBN 978-0-367-49303-5<https://www.giappichelli.it/computational-finance> For more info: https://www.francescocesarone.com/books -- Francesco Cesarone - Ph.D. Associate Professor Department of Business Studies Roma Tre University Via Silvio D'Amico, 77 00145 - Roma, Italy tel: +39 06 57335744 Skype: francesco.cesarone email: francesco.cesarone(a)uniroma3.it<mailto:francesco.cesarone@uniroma3.it> Studio n. 20 piano V WWW: https://www.francescocesarone.com/

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OWABC Seminar: Mark Beaumont - 30th May 9am UK time
by Massimiliano Tamborrino 14 May '24

14 May '24

Dear all, the last OWABC www.warwick.ac.uk/oneworldabc<http://www.warwick.ac.uk/oneworldabc> seminar of Season 5 is quickly approaching. We are glad to announce that our next speaker is Mark Beaumont (University of Bristol), who will talk about "Model misspecification in population genomic" on Thursday the 30th May at 9am UK time. Abstract: In likelihood-free settings, problematic effects of model misspecification can manifest themselves during computation, leading to nonsensical answers, particularly causing convergence problems in sequential algorithms. This issue has been well studied in the last 10 years, leading to a number of methods for robust inference. In practical applications, likelihood-free methods tend to be applied to the output of complex simulations where there is a choice of summary statistics that can be computed. One approach to handling misspecification is to simply not use summary statistics computed from simulations of the model under the prior that cannot be matched with those observed in the data. This presentation gives a brief review of methods for observing and handling misspecification in ABC and SBI, and then discusses approaches that we have explored in a population genomic modelling framework. The talk will be streamed on MS Teams, at the link https://teams.microsoft.com/l/meetup-join/19%3ameeting_NWFkYmE2MTgtZTNiNS00… Meeting ID: 349 104 341 838 Passcode: YxPUhR We are looking forward to seeing you at the next OWABC Seminar, best, Massimiliano on the behalf of the OWABC Seminar Organisers ------ Dr. Massimiliano Tamborrino Associate Professor and Warwick International Higher Education Academy (WIHEA) Fellow Department of Statistics University of Warwick https://warwick.ac.uk/tamborrino

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Richiesta annullamento iscrizione
by Fabiana Mancini 14 May '24

14 May '24

Salve, Potrei gentilmente essere tolta dalla mailing list di random? L'indirizzo è fabiana.mancini(a)hotmail.it Grazie! Inviato da Outlook per Android<https://aka.ms/AAb9ysg>

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talk Prof. Nacira Agram on May 23, 2024
by Emanuela Rosazza Gianin 14 May '24

14 May '24

Dear all, you are all invited to participate to the following seminar on *Thursday 23th of May 2024 at 15:00* in Aula Seminari Demografica 2062 at University of Milano Bicocca (via degli Arcimboldi 8, Milano - building U7, 2nd floor): Speaker: *Nacira Agram (KTH Stockholm)* Titolo: *Deep learning for conditional McKean-Vlasov Jump diffusions* Abstract: My talk focuses on using deep learning methods to optimize the control of conditional McKean-Vlasov jump diffusions. We begin by exploring the dynamics of multi-particle jump-diffusion and presenting the propagation of chaos. The optimal control problem in the context of conditional McKean-Vlasov jump-diffusion is introduced along with the verification theorem (HJB equation). A linear quadratic conditional mean-field (LQ CMF) is discussed to illustrate these theoretical concepts. Then, we introduce a deep-learning algorithm that combines neural networks for optimization with path signatures for conditional expectation estimation. The algorithm is applied to practical examples, including LQ CMF and interbank systemic risk, and we share the resulting numerical outcomes. Based on joint work with Jan Rems. Best wishes, Emanuela ****************************************** Emanuela Rosazza Gianin Dipartimento di Statistica e Metodi Quantitativi Università di Milano-Bicocca Tel. 02 64483208 e-mail: emanuela.rosazza1(a)unimib.it ******************************************

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Advances in Time Series Econometrics, Venice, May 17th, 2024
by Roberto CASARIN 14 May '24

14 May '24

Dear you all, the Econometrics group and the VERA centre of the Ca’ Foscari University ( https://www.unive.it/pag/35190) invite you to *Advances in Time Series Econometrics* *Half-day Workshop* *Venice May 17th, 2024Ca’ Foscari University, San Giobbe Campus, Meeting Room 1, Venezia* Program: - 9:30-10:15, *Ovielt Baltodano Lopez*, (Ca' Foscari University of Venice), Heterogeneous dynamic stochastic block models and an application to international trade - 10:15-11:00, *Alexander Simon Mayer* (Ca' Foscari University of Venice), Least squares estimation in nonstationary nonlinear cohort panels with learning from experience - 11:00-11:30, Break - 11:30-12.15, *Dario Palumbo* (Ca' Foscari University of Venice), A simple parsimonious framework for extracting and modelling the term structure of interest rates - 12:15-13:30, *Esther Ruiz* (University Carlos III of Madrid), Economic activity and climate change *Abstracts*: Ovielt Baltonado Lopez, Ca' Foscari University of Venice, Italy, https://www.unive.it/data/people/18754547 Heterogeneous dynamic stochastic block models and an application to international trade *The increasing complexity of the global economy represents a challenge for monitoring public debt risks. We propose a twofold framework by applying a Dynamic stochastic block model to a multi layer network composed of extracted debt relationships and trade ows for European countries. On the one hand, this approach allows for clusters of countries with di erent levels of debt synchronization that evolve over time and are subject to structural changes suggesting an increase in systemic risk. On the other hand, the layer dependence accounts for con icts in macroeconomic objectives. In particular, external balance and scal stability. In this sense, the network approach jointly considers interdependence between countries and the twin de cit phenomenon coherent with the composite nature of the risks in the nancial systems. We nd evidence of structural changes in the topology of the debt network during crisis, from an assortative behavior to a coreperiphery system with high interdependence among countries' debt. Moreover, the results suggest parameter heterogeneity. In stable periods unemployment (real GDP per capita) di erences lead to higher (lower) debt synchronization, while income inequality and nancial depth reduce the similarity in the debt evolution. There is no evidence of twinde cit phenomenon for the period 2003-2023.* Alexander Simon Mayer, Ca' Foscari University of Venice, Italy, https://www.unive.it/data/people/26394407 Least squares estimation in nonstationary nonlinear cohort panels with learning from experience *We discuss techniques of estimation and inference for nonstationary nonlinear cohort panels with learning from experience, showing, inter alia, the consistency and asymptotic normality of the nonlinear least squares estimator used in empirical practice. Potential pitfalls for hypothesis testing are identified and solutions proposed. Monte Carlo simulations verify the properties of the estimator and corresponding test statistics in finite samples, while an application to a panel of survey expectations demonstrates the usefulness of the theory developed.* Dario Palumbo, Ca' Foscari University of Venice, Italy, https://www.unive.it/data/people/22437798 A simple parsimonious framework for extracting and modelling the term structure of interest rates *This paper introduces a novel methodology for the extraction and modelling of the unobserved term structure of interest rates which incorporates in a single inferential framework both cross-sectional and time-series information from observed bond prices. In doing so, the paper introduces both a parametric and a semi-parametric dynamic model for the term structure which can be extended to capture also features such as heteroschedasticity in both the time and cross-section dimension, as well as the zero-lowerbound constraint. The models provide a coherent description of the term structure and outperforms current term structure extraction methods in fitting the observed bond prices surface. The models also outperform other existing dynamic term structure models in forecasting observed bond prices at one, six and twelve months horizons. Moreover, the study highlights a strong sensitivity of the forecasting errors of the existing dynamic models to the choice of the term structure extraction method used to construct the samples for the parameters’ estimation.* Prof. Esther Ruiz, University Carlos III of Madrid, Spain, https://researchportal.uc3m.es/display/inv16189 Economic activity and climate change -- Roberto Casarin, PhD Professor of Econometrics Ca' Foscari University of Venice San Giobbe 873/b - 30121 Venezia, Italy http://sites.google.com/view/robertocasarin/ https://www.unive.it/vera <https://www.unive.it/isba2024> https://www.unive.it/isba2024

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seminario di Brzeźniak a Pavia - 22 maggio ore 11
by Benedetta Ferrario 13 May '24

13 May '24

Mercoledì 22 maggio presso il Dipartimento di Scienze Economiche e Aziendali dell'Università di Pavia il professor Z. Brzezniak (Università di York) terrà un seminario alle ore 11 (precise) in aula 14. Title: Reflection of Stochastic Evolution Equations in Infinite Dimensional Domains Abstract: In this paper, we establish the existence and the uniqueness of solutions of stochastic evolution equations (SEEs) with reflection in an infinite dimensional ball. Our framework is sufficiently general to include e.g. the stochastic Navier-Stokes equations. Based on a joint work with Tusheng Zhang (Manchester and Hefei).

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Seminar Dario Trevisan at Tor Vergata 22.05
by Michele Salvi 13 May '24

13 May '24

Dear all, On Wednesday, May 22nd, at 14h30 in Aula Dal Passo of Tor Vergata Math Department, RoMaDS (https://www.mat.uniroma2.it/~rds/events.php) will host Dario Trevisan (Università di Pisa) with the seminar "Gaussian Approximation and Bayesian Posterior Distribution in Random Deep Neural Networks” Abstract: We establish novel rates for the Gaussian approximation of randomly initialized deep neural networks with Gaussian parameters and Lipschitz activation functions, in the so-called wide limit, i.e., where the sizes of all hidden layers become large. Using the Wasserstein metric and related functional analytic tools, we demonstrate the distribution of the output of a network and the corresponding Gaussian approximation are at a distance that scales inversely with the width of the network, surpassing previously established rates. Furthermore, we extend our findings to approximate the exact Bayesian posterior distribution of the network when the likelihood is a bounded Lipschitz function of the network output, on a finite training set. This includes common cases, such as the Gaussian likelihood, which is defined as the exponential of the negative mean squared error. Our inequalities thus shed light on the network's Gaussian behavior by quantitatively capturing the distributional convergence results in the wide limit. The exposition will aim to be self-contained, by introducing all the basic concepts related to artificial neural networks and Bayesian statistics to a mathematical audience. Based on arXiv:2203.07379 (joint with A. Basteri) and arXiv:2312.11737. We encourage in-person partecipation. Should you be unable to come, here is the link to the Teams streaming: https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw… The seminar is part of the Excellence Project MatMod@TOV.

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