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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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MSc scholarships at Université Paris-Est
by Tiziano De Angelis 13 May '24

13 May '24

Dear All, I am forwarding a message from Damien Lamberton concerning MSc scholarships for students interested in pursuing an MSc from the Université Paris-Est. The full advert is below. Please notice the tight deadline on 20 May. Best wishes Tiziano ---------- Forwarded message --------- > Da: Damien Lamberton <damien.lamberton(a)univ-eiffel.fr> > Date: mar 7 mag 2024 alle ore 17:04 > Subject: Fwd: [umr8050] Candidatures au M2 Bézout > To: Tiziano De Angelis <tiziano.deangelis(a)unito.it> > > > > > Dear Tiziano, > > I am forwarding some advertisement about our master's scholarships, in > case some of your students could be interested.. > > All the best, > > Damien > > > > ———————————————————————————————————————————————————————— > > > > Dear colleague, > > The 2024-2025 hiring campaign for international Bézout master's > scholarships is open from March 20 to May 20 at midnight. We will be able > to accept 10 applications. The Bézout scholarship program is directed > towards excellent students in mathematics, computer science or both, from > foreign institutions willing to pursue their studies in Université > Paris-Est at the master level. The laureates will receive about 1300 € per > month over 11 months and will be proposed a room on the campus. The best > students will then be invited to join the PhD program of the Doctoral > School MSTIC (Mathematics, Sciences and Information and Communication > Technology). A joint supervision with the student's national doctoral > framework, leading to both PhD grades, is possible. > > The details of the program can be found here: > https://labex-bezout.fr/masters-scholarships/ . From the same webpage, a > link to the application form will be available soon. > > A description of the activities of the Bézout Labex can be found in the > attached leaflet. One can also send you a few printed leaflets at your > postal address if you wish. > > Contact: Raphaël Danchin <danchin(a)u-pec.fr> > > > >

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Special Day on "Matrix models for quantum systems" - Friday June 7th at IHES
by Matteo D'Achille 13 May '24

13 May '24

Dear colleagues, I would like to draw your attention to the upcoming conference Matrix models for quantum systems, to be held on June 7th at the IHES in Bures-sur-Yvette. This conference is organized by the Seed Seminar of Mathematics and Physics <https://seedseminar.apps.math.cnrs.fr/>. The aim of the conference, and of the seminar in general, is to foster interactions between the mathematics and theoretical physics communities on topics of common interest. We will have the pleasure to listen to the following speakers: Guillaume Aubrun (Institut Camille Jordan, Lyon) Philippe Biane (Laboratoire d'Informatique Gaspard Monge, Marne-la-Vallée) Bertrand Eynard (Institut de Physique Théorique, CEA Saclay) Vladimir Kazakov (Laboratoire de Physique de l'École Normale Supérieure, Paris) The talks will be from 10:00 to 16:30, with a welcome coffee from 9:30. Both in-person and online participation are free but limited. Please register at https://indico.math.cnrs.fr/event/12052 if you are planning to participate in either capacity. Thank you for your attention and kind regards. Matteo D’Achille, for the organizing committee ---------------------------------- Matteo D’Achille, PhD Laboratoire de Mathématiques d’Orsay - LMO (UMR 8628 CNRS) Équipe Probabilités et Statistiques Bâtiment 307, rue Michel Magat, Faculté des Sciences d’Orsay, Université Paris-Saclay, F-91405 Orsay Cedex Office 3I20 (+33) 01 69 15 68 38 https://www.imo.universite-paris-saclay.fr/~matteo.dachille/

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(PMS)^2 talk - J. Janák - may 16 at 11:15
by Carlo Orrieri 13 May '24

13 May '24

Dear colleagues, we are happy to announce the following talk Josef Janák (Università di Pavia) Parameter estimation for the stochastic heat equation with multiplicative noise from local measurements Abstract: We propose the stochastic heat equation driven by the multiplicative space-time white noise and we introduce several estimators to the diffusivity parameter that are inspired by the maximum likelihood estimator. Since our observation scheme relies on local measurements, the asymptotics of the estimators is pursued with a fixed time horizon and with the spatial resolution of the observations tending to zero. A stable central limit theorem shows that our proposed estimators are strictly consistent and asymptotically mixed normal. The performance of the estimators is demonstrated in numerical simulations. This is a joint work with Professor Markus Reiß. Date and time: Thursday May 16, 11:15-12:15 (Rome time zone) Place: Aula Beltrami, Dip. Matematica, Univ. Di Pavia. Zoom meeting link: https://zoom.us/j/95472715600?pwd=bG1lYVNFMXp5ZGxBcTFoNXNxbE1UZz09 <https://zoom.us/j/95472715600?pwd=bG1lYVNFMXp5ZGxBcTFoNXNxbE1UZz09> ID riunione: 954 7271 5600 Codice d’accesso: 043885 These talks are part of the (PMS)^2: Pavia-Milano Seminar series on Probability and Mathematical Statistics organized jointly by the universities Milano-Bicocca, Pavia and Milano-Politecnico. Participation is free and welcome! Best regards The organizers (Carlo Orrieri, Maurizia Rossi, Margherita Zanella)

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Seminario ALOS - May 17th
by Alessandro Ramponi 13 May '24

13 May '24

Dear All, on May 17th, at 15:00, in classroom A (Building B), Department of Economics and Finance, University of Roma Tor Vergata, the following seminar will take place: Speaker: Elisa Alos (Dpt. Economia i Empresa, UPF, Barcelona) Title: On the Skew and Curvature of the Implied and Local Volatilities Abstract: In this talk, we study the relationship between the short-end of the local and the implied volatility surfaces. Our results, based on Malliavin calculus techniques, recover the recent 1/(H+3/2) rule (where H denotes the Hurst parameter of the volatility process) for rough volatilities (see F. Bourgey, S. De Marco, P. Friz, and P. Pigato, 2022), that states that the short-time skew slope of the at-the-money implied volatility is 1/(H+3/2) of the corresponding slope for local volatilities. Moreover, we see that the at-the-money short-end curvature of the implied volatility can be written in terms of the short-end skew and curvature of the local volatility and vice-versa. Additionally, this relationship depends on H.

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Padova Seminars in Probability and Finance - Domenico Marinucci - 14:30, May 17th
by Alberto Chiarini 13 May '24

13 May '24

Dear all, It is our pleasure to invite you all to the Padova Seminars in Probability and Finance on May, 17th at 14:30, at the department of Mathematics in Padova for the seminar by: Domenico Marinucci (University of Rome "Tor Vergata") Title: Geometry and Topology of Spin Random Fields Date: May 17, 2024, at 14:30, 2AB45 Abstract: Spin random fields are very important in many physical applications; they can be viewed as random sections of the s-th complex tensor power of the tangent bundle of the 2-sphere. In this talk, we discuss how to characterize their expected geometry and topology. In particular, we investigate the asymptotic behaviour, under scaling assumptions, of general classes of geometric and topological functionals for (properly defined) excursion sets; we cover both the cases of fixed and diverging spin parameters s. In the special case of monochromatic fields (i.e., spin random eigenfunctions), we show how their asymptotic behaviour is non-universal; we can obtain complex versions of Berry's random waves and of Bargmann-Fock's model as subcases of a new general class, depending on the rate of divergence of the spin parameter. We shall also discuss how these random fields can be reparametrised into complex-valued random functions on the group of rotations SO(3), and we discuss the expected values of the same geometric functionals in this new framework. Based on joint works with Javier Carròn Duque, Antonio Lerario, Maurizia Rossi and Michele Stecconi. Best wishes, Alberto and Alekos

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SPASS Seminar: Yassine Tahraoui
by Francesco Grotto 13 May '24

13 May '24

Dear Colleagues, We would like to invite you to the following SPASS seminar, jointly organized by UniPi, SNS, UniFi and UniSi: *Stochastic obstacle problems: variational & non variational settings* by Yassine Tahraoui (Scuola Normale Superiore) The seminar will take place tomorrow TUE, 14.05.2024 at 14:00 CET in Aula Seminari, Dipartimento di Matematica, UNIPI and streamed online at the link below. The organizers, A. Agazzi, G. Bet, A. Caraceni, F. Grotto, G. Zanco https://sites.google.com/unipi.it/spass *---------------------------------------------------------* *Abstract: Obstacle problems are free boundary type problems, well known in the literature of applied mathematics and lead to numerous applications. My aim is to present some results about the well-posedness and the regularity of the solution to a "parabolic or hyperbolic" obstacle problem in the presence of multiplicative noise, studied in [1, 2]. After showing the well-posedness of such problems, we prove Lewy-Stampacchia's inequalities, which gives an estimate of the reflected measure generated by the singularities caused by the obstacle near the free boundary.* *[1]I. H. Biswas, Y. Tahraoui and G. Vallet: Obstacle problem for a stochastic conservation law and Lewy-Stampacchia inequality. Journal of Mathematical Analysis and Applications, 527 (1) 127356 (2023)* *[2]Y. Tahraoui and G.Vallet: Lewy-Stampacchia's inequality for a stochastic T-monotone obstacle problem. Stochastic Partial Differential Equations: Analysis and Computations 10, 90-125 (2022).*

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Seminar in Statistics - ALEX MUNK
by Pierpaolo De Blasi 13 May '24

13 May '24

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 17 Maggio 2024, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: Alex Munk (Georg August Universitat Gottingen) Title: *Optimal Transport Dependency* Abstract: Finding meaningful ways to determine the dependency between two random variables 𝜉 and 𝜁 is a timeless statistical endeavor with vast practical relevance. In recent years, several concepts that aim to extend classical means (such as the Pearson correlation or rank-based coefficients like Spearman’s 𝜌) to more general spaces have been introduced and popularized, a well-known example being the distance correlation. In this talk, we propose and study an alternative framework for measuring statistical dependency, the transport dependency 𝜏 ≥ 0 (TD), which relies on the notion of optimal transport and is applicable in general Polish spaces. It can be estimated via the corresponding empirical measure, is versatile and adaptable to various scenarios by proper choices of the cost function. It intrinsically respects metric and geometric properties of the ground spaces. Notably, statistical independence is characterized by 𝜏 = 0, while large values of 𝜏 indicate highly regular relations between 𝜉 and 𝜁 . Based on sharp upper bounds, we exploit three distinct dependency coefficients with values in [0, 1], each of which emphasizes different functional relations: These transport correlations attain the value 1 if and only if 𝜁 = 𝜑(𝜉), where 𝜑 is a) a Lipschitz function, b) a measurable function, c) a multiple of an isometry. Besides a conceptual discussion of transport dependency, we address numerical issues and its ability to adapt automatically to the potentially low intrinsic dimension of the ground space. Monte Carlo results suggest that TD is a robust quantity that efficiently discerns dependency structure from noise for data sets with complex internal metric geometry. The use of TD for inferential tasks is illustrated for independence testing on a data set of trees from cancer genetics. Joint work with Giacomo Nies and Thomas Staudt. ------------------------------------------------ Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/81354066852?pwd=a2hEZTFHMDRuZHVYQ1RGSmd0Wi82QT09> 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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Seminario Karel Hron presso Politecnico di Milano
by Laura Maria Sangalli 12 May '24

12 May '24

Si avvisa che in data 15-05-2024, alle ore 11:00 precise al Politecnico di Milano, in aula Saleri (sesto piano Dipartimento di Matematica - edificio 14), si svolgerà il seguente seminario Karel Hron, University Olomouc Titolo: Analysing multivariate densities in Bayes spaces with implications for functional data analysis Abstract: Probability density functions can be embedded in the geometric framework of Bayes spaces which respect their relative nature and enable further modeling and analysis. Specifically, the Hilbert space structure of Bayes spaces (whereof compositional data are one specific instance) has several important implications for classical and Bayesian inference, as well as functional data analysis. In this contribution, an orthogonal decomposition of multivariate densities in Bayes spaces using a distributional analog of the Hoeffding-Sobol identity is constructed. The decomposition is based on a reformulation of the standard (arithmetic) margins into so-called geometric margins. These are orthogonal projections into one-dimensional space of information contained in multivariate densities and coincide with the arithmetic margins in case of independence. More generally, the decomposition contains an independent part and all possible interaction terms. The orthogonality of the decomposition results in an analog of Pythagoras' Theorem for squared norms of the decomposed densities and margin-free property of the interaction terms. Because the squared norms from the Pythagoras' decomposition are essentially compositional in nature, all tools of the log-ratio methodology can be used for their statistical processing. Theoretical results will be illustrated with empirical geochemical data. This talk is based on joint work with Christian Genest and Johanna Nešlehová from McGill University, Montréal, Canada. Il link per seguire il seminario online sarà reso disponibile pochi minuti prima dell’avvio del seminario al seguente link https://mox.polimi.it/mox-colloquia-seminars-list/mox-seminars/?id_evento=2… Tutti gli interessati sono cordialmente invitati a partecipare, Laura Sangalli —— Laura Maria Sangalli MOX - Dipartimento di Matematica Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano - Italy (+39) 02 2399 4554 laura.sangalli(a)polimi.it<mailto:laura.sangalli@polimi.it> https://sangalli.faculty.polimi.it

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International Conference in Venice - CALL FOR PAPERS
by Monica Billio 12 May '24

12 May '24

23nd INTERNATIONAL CONFERENCE CREDIT 2024 *The frontiers of new risks: AI, digital and sustainability transitions * Venice, Italy 3 – 4 October 2024 * * *GRETA Associati* (Venice, Italy),*CRIF* (Bologna, Italy), *European Datawarehouse *(Frankfurt am Main, Germany), *European Investment Fund* (Luxembourg), *Intesa Sanpaolo* (Milan, Italy) and *Modefinance* (Trieste, Italy) are partners in organising a Conference to be held in Venice on October 3-4, 2024. * * The CREDIT 2024 conference will bring together academics, practitioners and PhD students working in various areas of financial and socio-economic risk with the aim of creating a unique opportunity for participants to discuss research progress and policy as well as industry-relevant insights and directions for future research. CREDIT 2024 is the *twenty-third* in a series of events dedicated to various aspects of credit risk and organised under the auspices of: the *Department of Economics *and*VERA - Venice centre in Economic and Risk Analytics for public policies* - of the *Ca’ Foscari University of Venice*,*Joint Research Center European Commission*, *ABI - Italian Banking Association*, *AIAF - Associazione Italiana per l'Analisi Finanziaria*, *AIFIRM - Associazione Italiana Financial Industry Risk Managers*. Sustainability necessarily involves the adaptation of today’s business model to the dynamic nature of the current digitalised environments. Corporations need to make sure that resources, especially technology, are being used responsibly and efficiently to improve the lives of the present generations and future generations as well as strengthen their relationships with the environment as to solve sustainability-related problems such as poverty, environmental degradation, pollution and inequality. Artificial Intelligence (AI) has the potential to address these societal problems including sustainability. The climate crisis and the degradation of the physical environment are complex problems that require the most innovative and advanced solutions. The real value of AI hence lies in its ability to facilitate and foster environmental and social governance, rather just as a tool to reduce pollution, poverty and resource depletion. In the age of AI, societies depend on big data, social media, knowledge management and data science to survive and achieve these sustainability goals. AI has the potential to reshape not only finance and industry but also the whole society. There is need to understand opportunities and challenges as to properly manage all relevant risks. The organisers encourage submissions on any topic within the overall theme of the conference, with attention to *the use of AI to assess the sustainability impact of finance *(i.e. exploiting AI techniques or Big Data to bridge primary information gaps and proxy the sustainability impact) and *on how climate and digital risks may interact* (i.e. climate denial, social media and social media strategies including deepfakes). The final program will include both submitted and invited papers. Acceptances received so far from invited speakers include *Patrick Bolton *(Imperial College London), and *Roberto Rigobon* (MIT Sloan School of Management). The Conference will also include panel discussions on the major issues at stake with the views of researchers', practitioners' and policy makers. The SCIENTIFIC COMMITTEE for the Conference consists of: *Marcin Kacperczyk *(Imperial College London, Programme Chair) *Monica Billio* (Ca’ Foscari University of Venice & GRETA) *Marie Brière* (AMUNDI & Université Libre de Bruxelles) *Lucia Alessi* (Joint Research Center, European Commission) *Leonardo Gambacorta *(Bank For International Settlements) *Mila Getmansky* (Isenberg School of Management, UMass Amherst) *Christian Gollier* (Toulouse School of Economics) *Helmut Kraemer-Eis *(European Investment Fund) *Jan Pieter Krahnen *(Leibniz Institute for Financial Research SAFE & Goethe University) *Steven Ongena* (University of Zurich, Swiss Finance Institute, KU Leuven, NTNU Business School & CEPR) *Roberto Rigobon *(MIT Sloan School of Management) *Stephen Schaefer* (London Business School) *Marti Subrahmanyam *(NYU Stern Business School) CALL FOR PAPERS Those wishing to present a paper at the Conference should submit by *June 10, 2024 *to the address given below (preferably in electronic format). Please indicate to whom correspondence should be addressed. Decisions regarding acceptance will be made by July 10, 2024. The final version of accepted papers must be received by August 31, 2024. Please send papers to: GRETA Associati, Dorsoduro 3707 - 30123 Venice, ITALY Phone : +39 349 060 3656 - e-mail: credit(a)greta.it More detailed information on the Conference website: https://www.greta.it/index.php/it/credit-2024

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Seminar RUSSO
by Stefano Pagliarani 10 May '24

10 May '24

Dear all, On May 15th, at 11 am, in the classroom Aula Seminari VIII Piano, Department of Mathematics of the University of Bologna, Francesco RUSSO will give a seminar entitled WEAK DIRICHLET PROCESSES AND BSDE<https://www.dm.unibo.it/seminari/mat/seminars/2024/05/15/francesco-russo>s The abstract is available at https://www.dm.unibo.it/seminari/mat/seminars/2024/05/15/francesco-russo For any question, please contact the organizers: Cristina di Girolami and Stefano Pagliarani. Best regards, ------------------------------------------------------------------------------------------------------------------------ Stefano Pagliarani, Associate Professor Piazza di Porta S. Donato, 5 University of Bologna (Alma Mater) 40126 Bologna (BO), Italy Department of Mathematics Cell. Phone +39 366 5013755 Email: stepagliara1(a)gmail.com<mailto:stepagliara1@gmail.com>, <mailto:stefano.pagliarani9@unibo.it> stefano.pagliarani9(a)unibo.it<mailto:stefano.pagliarani9@unibo.it> Zoom: https://unibo.zoom.us/j/3755841669 -----------------------------------------------------------------------------------------------------------------------

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Fwd: Summer School Ischia ESI
by Roy Cerqueti 09 May '24

09 May '24

Dear all, please, find the flyer of this Summer School, that can be of interest to some young scholars. Thank you. Yours sincerely, Roy Cerqueti -- *Fai crescere le giovani ricercatrici e i giovani ricercatori*** *con il 5 per mille alla Sapienza* Scrivi il codice fiscale dell'Università *80209930587 **Cinque per mille <https://www.uniroma1.it/it/node/23149>*

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Fwd: Next LTI@Unito Seminar: Stéphane Villeneuve | May 13 @ 12:00 - 13:00
by Luca Regis 08 May '24

08 May '24

Dear colleagues, please find below the announcement of the seminar by Stephane Villeneuve (TSE) organized by LTI@UniTO and Collegio Carlo Alberto. The seminar can be attended via zoom clicking on the button below. Best regards, Luca Regis ---------------------------------------- Associate Professor ESOMAS Department, University of Torino Affiliate, Collegio Carlo Alberto sites.google.com/view/lucaregis Office: +39 011 670 6065 www.carloalberto.org/lti Next LTI@Unito Seminar: Stéphane Villeneuve | May 13 @ 12:00 - 13:00 <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeFuBop7S3TtlKvKzHBSs/4oJ_v…> LTI@UniTO and Fondazione Collegio Carlo Alberto are pleased to invite you to the following seminar: *May 13, 2024 | 12:00 - 13:00* *Dynamic contracting with many agents* *Stéphane Villeneuve (Toulouse School of Economics)* *Abstract: *We analyze dynamic capital allocation and risk sharing between a principal and many agents, who privately observe their output. The state variables of the mechanism design problem are aggregate capital and the distribution of continuation utilities across agents. This gives rise to a Bellman equation in an infinite dimensional space, which we solve with mean-field techniques. We fully characterize the optimal mechanism and show that the level of risk agents must be exposed to for incentive reasons is decreasing in their initial outside utility. We extend classical welfare theorems by showing that any incentive-constrained optimal allocation can be implemented as an equilibrium allocation, with appropriate money issuance and wealth taxation by the principal. To attend online, join Zoom meeting <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeG13GxwPEe3FQkdjFU38/HGpf3…> *Fondazione Collegio Carlo Alberto* Piazza Arbarello 8 - 10122 Torino, Italy phone: +3901115630800 <tel:+3901115630800> segreteria(a)carloalberto.org - www.carloalberto.org <https://4z5y5.r.sp1-brevo.net/mk/mr/sh/SMJz09SDriOHWoY4zxneDRikeAJG/JT1digZ…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeG7uj6lMPoCjWZwTDmdO/xbd5a…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGEmBFaJayMDcPFDC5De/7R5hd…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGLddOPGm8VhiEXxANnu/KmFdZ…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGSV5XEDxIfBo3qh8gOA/THQZY…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGZMXg3B8Softt9R6yyQ/xDNI-…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGgDzos8Jcy9ziSB5HYg/jDbOw…> *Founders* <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGn5Rxh5Un7e5Xkv3a8w/r0Vb5…> <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/SMK1E8tHeGtwu6W2fxH8BN3f1sjC/phw27…> *Sostieni il Collegio Carlo Alberto con il 5x1000 | c.f. 94049090015* *INFORMATION UNDER THE NEW GENERAL DATA PROTECTION REGULATION (GDPR)* Your personal information has been gathered for the exclusive purpose of informing you about the Collegio's initiatives, considering our and your legitimate interest or your consent. If you wish to have your personal data modified please contact Fondazione Collegio Carlo Alberto, piazza Arbarello 8, 1022 Torino, Italy - phone:+39011 15630 800 - privacy(a)carloalberto.org <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/1t6Af4OiGsDhYHezxFlTns9XmrPqba/o-w…> To find out about the policies regarding the processing of personal data pursuant to articles 13-14 of EU Regulation 2016/679, consult the information at the following link _https://www.carloalberto.org/privacy/_ <https://4z5y5.r.sp1-brevo.net/mk/cl/f/sh/1t6Af4OiGsE9szrQLbrOy8DNAgOaJe/Drj…> *Unsubscribe* <https://4z5y5.r.sp1-brevo.net/mk/un/sh/SMJz09a0vkbXsu1klhxRMEbrtrvO/3tb3NOW…> *© 2022 Fondazione Collegio Carlo Alberto*

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STATISTICAL REFLECTIONS: Half-day Workshop on Statistical Methods - Ca’ Foscari University (Scientific Campus Venezia Mestre)
by Carlo Gaetan 08 May '24

08 May '24

Dear all, the STREAM group (https://www.unive.it/pag/16818/) of the Ca’ Foscari university invites to *STATISTICAL REFLECTIONS* *Half-day Workshop on Statistical Methods* *Venice May 22, 2024* Ca’ Foscari University Scientific Campus Aula Delta 1B Via Torino 155 Venezia Mestre Program: -14:00 David Firth (University of Warwick): Compositional quasi-likelihood and logit models -14:45 Ioannis Kosmidis (University of Warwick): Consistent, tuning-free model selection in regression problems -15:30 Omiros Papaspiliopoulos (Bocconi University): Functional estimation of the marginal likelihood Abstracts: Professor David Firth University of Warwick, UK https://warwick.ac.uk/dfirth Compositional quasi-likelihood and logit models A composition vector describes the relative sizes of parts of a thing. Some important modern application areas are microbiome analysis, time-use analysis and archaeometry (to name just three). We develop model-based analysis of composition, through the first two moments of measurements on their original scale. In current applied work the most-used route to compositional data analysis, following an approach introduced by the late John Aitchison in the 1980s, is based on contrasts among log-transformed measurements. The quasi-likelihood model framework developed here provides a general alternative with several advantages. These include robustness to secondary aspects of model specification, stability when there are zero-valued or near-zero measurements in the data, and more direct interpretation. Linear models for log-contrast transformed data are replaced by generalized linear models with logit link, and variance-covariance estimation is straightforward via suitably standardized residuals. Joint work with Fiona Sammut, University of Malta. Professor Ioannis Kosmidis University of Warwick, UK https://www.ikosmidis.com Consistent, tuning-free model selection in regression problems We present a family of consistent model selection procedures for regression problems, which appropriately threshold readily available statistics after estimating the model with all covariate information. The model selection procedures rely only on standard assumptions about information accumulation that guarantee the typically expected asymptotic properties of the estimators (e.g., consistency) and require neither the selection of tuning parameters nor the fitting of all possible models. We apply our thresholding methodology in widely used statistical models (e.g. generalized linear models and beta regression), demonstrate that it is easily implementable as part of the standard maximum likelihood output, and compare its performance to existing techniques, illustrating its effectiveness. Joint work with Patrick Zietkiewicz, University of Warwick. Professor Omiros Papaspiliopoulos Bocconi University, Italy https://dec.unibocconi.eu/people/omiros-papaspiliopoulos Functional estimation of the marginal likelihood We consider the problem of exploring the marginal likelihood of low-dimensional hyperparameters from high-dimensional Bayesian hierarchical models. We provide a unified framework that connects seemingly unconnected approaches to estimating normalizing constants, including the Vardi estimator, the umbrella sampling and the Gibbs sampler. The framework requires Monte Carlo sampling from the posteriors of the high-dimensional parameters for different values of the hyperparameters on a lattice. We establish a surprising reproducing property that leads to a functional estimator of the marginal likelihood and establish consistency both fixed-lattice and lattice-infill consistency. The resultant method is highly practical, black-box with theoretical guarantees. Best regards, Carlo Gaetan -- - Dipartimento di Scienze Ambientali, Informatica e Statistica - DAIS Università Ca' Foscari - Venezia Z.A12 - Edificio Zeta Via Torino, 155 I-30172 Mestre (VE) ITALY phone: ++39 041 234 8404 e-mail:[gaetan"at"unive"dot"it] web:[http://www.dais.unive.it/~gaetan] Please don't print this e-mail unless you really need to. Please avoid sending me Word, Excel or PowerPoint attachments. Seehttp://www.gnu.org/philosophy/no-word-attachments.html. Per favore non stampate questo messaggio se non è proprio necessario. Per favore non mandatemi allegati in Word, Excel o PowerPoint. Le ragioni sono spiegate quihttp://www.gnu.org/philosophy/no-word-attachments.it.html

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Kolmogorov meets Turing - May 23, 11am - 6pm, DIAG, Sapienza, Rome
by Marco Scarsini 07 May '24

07 May '24

Kolmogorov meets Turing *Workshop on probabilistic methods for the analysis of stochastic processes and randomized algorithms* This year's edition of the Kolmogorov meets Turing Workshop will take place on Thursday, May 23rd 2024, at DIAG <https://www.diag.uniroma1.it/>, via Ariosto 25, Aula Magna I floor. The purpose of KmT is to bring together researchers from Computer Science, Economics, Mathematics and related fields to present and discuss research on probabilistic methods for the analysis of games, distributed and stochastic processes, dynamic processes and randomized algorithms. When: Thursday May 23rd, 2024 Where: Dipartimento di Ingegneria Informatica, Automatica e Gestionale “A. Ruberti”, via Ariosto 25, Roma – Aula Magna, I floor Schedule Morning session 11.00 – 12.00. Nicolò Cesa-Bianchi (Università degli Studi di Milano): The mathematics of machine learning: between statistics and game theory 12.00 – 12.30. Xavier Mathieu Raymond Venel (Luiss University): Weighted average-convexity in Cooperative Games 12.30 – 13.00. Guido Schaefer (CWI, Netherlands): To Trust or Not to Trust: Assignment Mechanisms with Predictions 13.00 – 14.30: Lunch break Afternoon session 14.30 – 15.00. Pietro Caputo (University Roma Tre): Nonlinear Monte Carlo dynamics for the Ising model: some convergence results 15.00 – 15.30. Matteo Quattropani (Sapienza University of Rome): Mixing of the Averaging process on graphs and hypergraphs 15.30 – 16.00. Robin Vacus (Bocconi University): Minority Dynamics: the Short and Winding Road to Consensus 16.00 – 16.30: Coffee break 16.30 – 17.00. Maria Sofia Bucarelli (Sapienza University of Rome): On Generalization Bounds for Projective Clustering 17.00 – 17.30. Francesco D'Amore (Bocconi University): The Strong Lottery Ticket Hypothesis and the Random Subset Sum Problem 17.30 – 18.00. Federico Fusco (Sapienza University of Rome): The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations _______________________________________________________ LIST OF ABSTRACTS Maria Sofia Bucarelli: On Generalization Bounds for Projective Clustering. Given a set of points, clustering consists of finding a partition of a point set into k clusters such that the center to which a point is assigned is as close as possible. Most commonly, centers are points themselves, which leads to the famous k-median and k-means objectives. One may also choose centers to be j dimensional subspaces, which gives rise to subspace clustering. In this paper, we consider learning bounds for these problems. That is, given a set of n samples P drawn independently from some unknown, but fixed distribution D, how quickly does a solution computed on P converge to the optimal clustering of D? We give several near p optimal results. In particular, 1) For center-based objectives, we show a convergence rate of O(√k/n). This matches the known optimal bounds of [Fefferman, Mitter, and Narayanan, Journal of the Mathematical Society 2016] and [Bartlett, Linder, and Lugosi, IEEE Trans. Inf. Theory 1998] for k-means and extends it to other important objectives such as k-median. 2) For subspace clustering with j-dimensional subspaces, we show a convergence rate of O(√kj2/n). These are the first provable bounds for most of these problems. For the specific case of projective clustering, which generalizes k-means, we show a converge rate of Ω(√kj/n) is necessary, thereby proving that the bounds from [Fefferman, Mitter, and Narayanan, Journal of the Mathematical Society 2016] are essentially optimal. Nicolò Cesa-Bianchi: The mathematics of machine learning: between statistics and game theory. Machine learning is the main driving force behind the current AI revolution. To provide a solid mathematical foundation to learning systems, we must formally characterize what a machine can learn and what is the minimal amount of training data needed to achieve a desired performance. In this talk, I will describe the two main approaches to algorithmic learnability, one rooted in statistics and one in game theory, and explore their connections. Pietro Caputo: Nonlinear Monte Carlo dynamics for the Ising model: some convergence results. We introduce and analyze a natural class of nonlinear Monte Carlo dynamics for spin systems such as the Ising model. The evolution is based on the framework of mass action kinetics, which models systems undergoing collisions, and captures a number of nonlinear models from various fields, including chemical reaction networks, Boltzmann’s model of an ideal gas, recombination in population genetics and genetic algorithms. In the context of spin systems, it is a nonlinear analog of the familiar Monte Carlo method based on Markov chains, such as Glauber dynamics and block dynamics, which are by now well understood. The nonlinearity makes the dynamics much harder to analyze, and even the most basic convergence issues are far from being settled. We discuss several open problems. The main result is an optimal estimate on the rate of convergence to stationarity in a regime of high temperature. Our analysis combines tools from percolation, branching and fragmentation processes. Based on joint work with Alistair Sinclair. Francesco D’Amore: The Strong Lottery Ticket Hypothesis and the Random Subset Sum Problem. The Strong Lottery Ticket Hypothesis (SLTH) posits that randomly-initialized neural networks contain subnetworks (strong lottery tickets) that achieve competitive accuracy when compared to sufficiently small target networks, even those that have been trained. Empirical evidence for this phenomenon was first observed by Ramanujan et al. in 2020, spurring a line of theoretical research: Malach et al. (ICML ’20), Pensia et al. (NeurIPS ’20), da Cunha et al. (ICLR ’20), and Burkholz (ICML & ICLR ’22) have analytically proved formulations of the SLTH in various neural network classes and under different hypotheses. In this presentation, we provide an overview of the state-of-the-art theoretical research on the SLTH and its connection with the Random Subset Sum (RSS) problem in theoretical computer science. While previous works on the SLTH ensure that the strong lottery ticket can be obtained via unstructured pruning, we demonstrate how recent advances in the multidimensional generalization of the RSS problem can be leveraged to obtain forms of structured pruning. Additionally, we highlight how refining the RSS results would yield tighter formulations of the SLTH. This presentation is based on a joint work with A. Da Cunha and E. Natale appeared at NeurIPS 2023. Federico Fusco: The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations. We study the problem of regret minimization for a single bidder in a sequence of first-price auctions where the bidder discovers the item’s value only if the auction is won. Our main contribution is a complete characterization, up to logarithmic factors, of the minimax regret in terms of the auction’s transparency, which controls the amount of information on competing bids disclosed by the auctioneer at the end of each auction. Our results hold under different assumptions (stochastic, adversarial, and their smoothed variants) on the environment generating the bidder’s valuations and competing bids. These minimax rates reveal how the interplay between transparency and the nature of the environment affects how fast one can learn to bid optimally in first-price auctions. The talk is based on a joint work with Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, and Stefano Leonardi, which will appear at STOC 2024. Matteo Quattropani: Mixing of the Averaging process on graphs and hypergraphs. The Averaging process is a mass redistribution process over the vertex set of a graph or, more generally, a hypergraph. Given a (hyper)graph G, the process starts with a non-negative mass associated with each vertex. At each discrete time step, one of the (hyper)edges of G is sampled at random and the total mass associated with the vertices of the chosen (hyper)edge is equally redistributed among its vertices. Clearly, as time grows to infinity, the state of the system will converge to a flat configuration in which all the vertices have the same mass. This very simple process appeared in different literatures under various names, and it was introduced to the probabilistic community by Aldous and Lanoue in 2012. However, until a few years ago, there were no sharp quantitative results on the time needed to reach equilibrium. Indeed, the analysis of this process requires different tools compared to the classical Markov chain framework, and even in the case of seemingly straightforward geometries—such as the complete graph or the cycle—it can be handled only by means of nontrivial probabilistic and functional analytic techniques. During the talk, I’ll give an overview of the problem and its difficulties, present the classes of examples that are currently settled, and mention some possible future directions of investigation. Based on joint work with Pietro Caputo and Federico Sau. Guido Schaefer: To Trust or Not to Trust: Assignment Mechanisms with Predictions. The realm of algorithms with predictions has led to the development of several new algorithms that leverage (potentially erroneous) predictions to enhance their performance guarantees. The challenge here is to devise algorithms that achieve optimal approximation guarantees as the prediction quality varies from perfect (consistency) to imperfect (robustness). This framework is particularly appealing in mechanism design contexts, where predictions might convey private information about the agents. In this talk, we present our recent results on the design of truthful mechanisms that leverage predictions to achieve improved approximation guarantees for several variants of the generalized assignment problem (GAP). We consider the private graph model introduced by Dughmi and Ghosh (2010), where the set of resources that an agent is compatible with is private information. We investigate GAP in the private graph model augmented with a prediction of the optimal assignment. We give a deterministic group-strategyproof mechanism that is (1 + 1/γ)-consistent and (1 + γ)-robust for the special case of bipartite matching, where γ ≥ 1 is some confidence parameter. We also prove that this is best possible. Remarkably, our mechanism draws inspiration from the renowned Gale-Shapley algorithm, incorporating predictions as a crucial element. For more general GAP variants, we introduce a unified greedy scheme and use randomization to derive universally group-strategyproof mechanisms that achieve improved consistency and robustness guarantees in expectation. Robin Vacus: Minority Dynamics: the Short and Winding Road to Consensus. The ”minority” rule is a peculiar opinion dynamics, which prompts agents to adopt the opinion least represented in a sample – in contrast to its far more famous and natural counterpart, the majority rule. Yet, as long as the sample size is large enough and communications happen in parallel, it proves to be an efficient way to reach agreement. Moreover, contrary to traditional consensus protocols, it demonstrates extreme sensitivity to even a small number of ”stubborn” individuals, enabling fast information propagation within the group. In this presentation, I will describe an analysis of convergence time, showcase simulation results, and discuss several open problems, shedding light on what is currently understood and what remains to be explored about this fascinating dynamic. This talk is based on a recent work with Luca Becchetti, Andrea Clementi, Francesco Pasquale, Luca Trevisan and Isabella Ziccardi, that was published in SODA 2024. Xavier Mathieu Raymond Venel: Weighted average-convexity in Cooperative Games. It is well known that the Shapley value of a convex game always belongs to the core. Looking for a weaker condition than convexity insuring that the Shapley value of a game lies in the core, Inarra and Usategui (1993) relaxed the convexity assumption by introducing the notion of average convexity. Assuming that weights are associated with the players, we generalize the notion of convexity and average-convexity for cooperative TU games to the notion of weighted average-convexity. We prove that if a game is weighted average-convex, then the corresponding weighted Shapley value is in the core. We then study the relations between weighted average-convexity, core-inclusion, and communication TU-games. We exhibit necessary and sufficient conditions on the underlying graph to preserve weighted average-convexity from any communication game to the associated Myerson restricted game, extending some previous results established in Slikker (1998). Joint work with Alexandre Skoda.

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Seminar Dr Frank Fu (MathWorks) - Roma Tre University
by Francesco Cesarone 07 May '24

07 May '24

Dear all, I am pleased to announce the upcoming seminar "MATLAB Applications in Finance<https://it.mathworks.com/company/events/seminars/matlab-applications-in-fin…>" held by Frank Fu, Academic Manager MathWorks, on May 17th, 2024. The seminar is part of a series (Friday Seminar Series) organized by the Research Group in Quantitative Finance, Department of Business Studies - Roma Tre University. It is aimed at students majoring in or interested in business, economics, and finance, lecturers, and professors who teach such subjects or do academic research in those areas. The seminar can be attended physically at the Computer Lab (small classroom) on the ground floor (Department of Business Studies - Roma Tre University, Via Silvio D'Amico, 77, 00145 Rome, Italy) or online via teams. Participation is free, but registration for the seminar is mandatory (link<https://it.mathworks.com/company/events/seminars/matlab-applications-in-fin…>). More information can be also found on the following webpage<https://www.francescocesarone.com/msc-in-finance/friday-seminar-series>. 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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Seminario di Federico Sau a Roma Tre il 14 maggio
by Pietro Caputo 07 May '24

07 May '24

Martedì* 14 Maggio* 2024 alle ore *14:30*, Federico Sau (Università degli Studi di Trieste) terrà il seminario di Probabilità dal titolo "*Scaling limits of the averaging process*". Abstract: The averaging process on a graph is a continuous-space Markov chain, which is commonly interpreted as an opinion dynamics, a distributed algorithm, or an interface moving through a randomized sequence of deterministic local updates. Its dynamics goes as follows. Attach i.i.d. Poisson clocks to edges, and assign real values to vertices; at the arrival times of these clocks, update the values with their average. As time runs, the averaging process converges to a flat configuration, and one major problem in the field is that of quantifying the speed of convergence to its degenerate equilibrium in terms of characteristic features of the underlying graph. In this talk, after reviewing some basic properties and recent results on mixing times for the averaging process on general graphs, we focus on the discrete $d$-dimensional torus, and on some finer properties of the process in this setting. We discuss some quantitative features (e.g., limit profile, early concentration and local smoothness), and look at nonequilibrium fluctuations, a particularly interesting problem in this degenerate context lacking a non-trivial notion of local equilibrium. If time permits, we will touch on the main ideas of the proof of such scaling limits, which combine tools from Malliavin calculus in Poisson space, their probabilistic dynamic interpretations, and some new discrete-gradient estimates. Talk based on the preprints arXiv.2311.14176, arXiv.2403.02032. Il seminario si svolgerà in presenza presso il Dipartimento di Matematica e Fisica - Lungotevere Dante 376 (Blocco Aule) - *Aula M2*

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RTT MAT/06 - Milano Statale
by Andrea Cosso 06 May '24

06 May '24

Buonasera, vi segnalo che è stato bandito un posto di ricercatore tenure-track (RTT) in MAT/06 presso il Dipartimento di Matematica dell’Università degli Studi di Milano. Il bando si trova al seguente link: https://www.unimi.it/it/ateneo/lavora-con-noi/reclutamento-ricercatori/sele… La scadenza per la presentazione delle domande è il 31 maggio 2024. Cordiali saluti, Andrea Cosso English version Dear colleagues, the Mathematics Department of the University of Milan has opened a position as tenure-track researcher (RTT) in the scientific sector MAT/06 (Probability and Mathematical Statistics): https://www.unimi.it/en/university/work-us/researcher-recruitment/researche… The deadline for applications is May 31, 2024. Best regards, Andrea Cosso

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