Diffondo molto volentieri
Dear Colleagues,
We are pleased to announce that the website for *the 10th conference on
BSDEs to be held in Shandong University, Qingdao, P.R. China, from June 26
to July 1, 2025*, is now ready:
https://bsde2025.conferencesvc.com/
Here, you may find:
- Key dates & submission guidelines
- Registration details
- Information on organizing sessions
- Updates on invited speakers (The list of confirmed **invited speakers**
will be updated on the website by the end of this month)
**Call for Participation:**
We warmly encourage you to:
✔ Submit proposals.
✔ Register early to secure your spot.
Best regards,
Juan Li
Shandong University, Weihai & Qingdao
On behalf of the local organizers.
--
Gianmario Tessitore
Dipartimento di Matematica e Applicazioni
Università degli Studi di Milano-Bicocca
Dear colleagues,
you are all invited to participate in the following seminar organized by QFinLab - Department of Mathematics, Politecnico di Milano.
Wednesday, 2 April 2025, 12.15-13.15
Seminar room, third floor, building 14, Via Bonardi 9, Milano (Leonardo Campus)
Claudio Fontana (Università di Padova)
Title: A stochastic Gordon-Loeb model for optimal security investment under clustered cyber-attacks.
Abstract: We propose a continuous-time extension of the Gordon-Loeb model for optimal investment in information security under the threat of cyber-attacks. The arrival of attacks is modeled using Hawkes processes, capturing the realistic feature of clustering in cyber-attacks. Each attack may lead to a system breach, with the probability of breach depending on the system's vulnerability. We aim at determining the optimal investment in cyber-security to reduce the system's vulnerability. The problem is formulated as a two-dimensional Markovian stochastic control problem and solved via dynamic programming techniques. We perform a numerical study of the value function and the associated optimal investment strategy in cyber-security, highlighting the impact of randomly arriving clustered cyber-attacks. Based on a joint work with G. Callegaro, C. Hillairet, B. Ongarato.
Next seminar: Alessandro Sbuelz (Università Cattolica del Sacro Cuore), 7 May 12.15.
All news can be found on the QFinLab webpage<https://www.qfinlab.polimi.it/seminars-and-meetings/>.
The organizers: Michele Azzone and Alessandro Calvia.
Dear Colleagues,
A new position (Assistant/Associate level) in *Statistical Learning *is
open at the *Department of Mathematics of Luxembourg University (DMATH)*.
Deadline for applications; *June 30th, 2025*
Here is a link to the official announcement:
http://emea3.mrted.ly/3uk09
With kind regards,
Giovanni Peccati
--
Prof. Giovanni Peccati
------------------------------------------
Head of the Department of Mathematics
Faculty of Science,
Technology and Medicine
------------------------------------------
University of Luxembourg
------------------------------------------
President of the Luxembourg
Mathematical Society
https://math.uni.lu/sml/
------------------------------------------
homepage:
http://sites.google.com/site/giovannipeccati/home
E-mail: giovanni.peccati(a)gmail.com
Diffondo volentieri
---------- Forwarded message ---------
Da: Stefan Geiss <geiss(a)jyu.fi>
Date: Mer 26 Mar 2025, 07:15
Subject: International Seminar on SDEs ... : Apr 11: Arnaud Debussche
To: <gianmario.tessitore(a)unimib.it>
Best regards, Stefan
Dear Colleague,
tomorrow, Friday, April 11 ,
(12:30 noon London, 1:30 pm Berlin, 2:30 pm Helsinki, 7:30 pm Beijing)
in the *International Seminar on SDEs and Related Topics* in Zoom
https://jyufi.zoom.us/j/61891007917
Apr 11, 2025
*Arnaud Debussche*
(ENS Rennes, France)
will speak about
*From correlated to white transport noise in fluid models*
Abstract: Stochastic fluid models with transport noise are popular, the
transport noise models unresolved small scales. The main assumption in
these models is a very strong separation of scales allowing this
representation of small scales by white - i.e. fully decorrelated -
noise. It is therefore natural to investigate whether these models are
limits of models with correlated noises. Also, an advantage of
correlated noises is that they allow classical calculus. In particular,
it allows to revisit the derivation of stochastic models from
variational principles and allows to derive an equation for the
evolution of the noise components. The advantage of having such an
equation is that in most works, the noise components are considered as
given and stationary with respect to time which is non realistic.
Coupling stochastic fluid models with these gives more realistic systems.
===== about the speaker ====
Arnaud Debussche is a prominent French mathematician specializing in
stochastic partial differential equations and their applications. Born
in 1965, he attended the École Normale Supérieure de Saint-Cloud,where
he pursued advanced studies in mathematics. He earned his Ph.D. from
Université d'Orsay in 1989. Following a postdoctoral position at Indiana
University, he joined the National Center for Scientific Research (CNRS)
in 1992. In 2000, he became a full professor at the École Normale
Supérieure de Rennes, where he continues to contribute significantly to
the field. Throughout his career, Professor Debussche has made
substantial contributions to the analysis and numerical simulation of
stochastic partial differential equations, particularly in fluid
dynamics. His work includes studies on the stochastic Navier–Stokes
equations and the stochastic nonlinear Schrödinger equation. He has also
co-edited scholarly works on stochastic partial differential equations,
reflecting his active engagement in advancing mathematical understanding
in this area. Professor Debussche's research has been widely recognized
and cited, underscoring his influence in the mathematical community. His
ongoing work continues to shape the study of stochastic processes and
their applications in complex systems.
========our webpage is ========================
https://users.jyu.fi/~chgeiss/271828.html
Carissime/i,
segnaliamo che lunedì 16 giugno presso il Dipartimento di Matematica
dell’Università di Pavia si terrà una giornata di seminari dal titolo
"One-day workshop on SPDEs"
La giornata è dedicata a Zdzislaw Brzezniak, che sarà ospite del
Dipartimento nel mese di giugno.
Ecco il link
<https://sites.google.com/unipv.it/workshop-spdes-2025/home-page> al sito
della conferenza, in cui trovate i dettagli.
La scadenza per la registrazione - obbligatoria per motivi organizzativi -
è il 2 maggio.
Arrivederci a Pavia!
Il comitato organizzativo
Franco Flandoli, Enrico Priola, Benedetta Ferrario
Dear all,
We are happy to invite you to the second *European Summer Program in
Infectious Disease Analysis and Modelling (*ESPIDAM*). *
*Time*: June 23-27, 2025
*Location*: Stockholm University, Sweden
*Registration Deadline*: May 31 (early birds: March 31)
*Suitable participants*: PhD students, PostDocs, Public Health scientists
and others interested
*Structure*: The summer program consists of 7 course modules of which
participants can attend one or two.
*More information*: www.math.su.se/espidam
*Contact: *espidam(a)math.su.se
*Advisory board:* Tom Britton (chair), Simon Cauchemez, Sebastian Funk, Niel
Hens, Mirjam Kretzschmar, Lorenzo Pellis
Please spread to others you think might be interested. The early
registration deadline is in one week.
Warmly welcome!
The local organising committee
Tom Britton, Martina Favero and Fanny Bergrström
Seminari on-line del gruppo UMI - PRISMA (http://www.umi-prisma.polito.it/)
I seminari PRISMA hanno un formato di "colloquium" per creare un'occasione
di scambio e discussione con tutta la comunità dei probabilisti e
statistici italiani. Ogni giornata comprende due relatori che tengono due
seminari di 30 minuti strettamente connessi, per presentare alla comunità
una prospettiva sul proprio ambito di ricerca. Da quest'anno le
registrazioni dei seminari vengono pubblicate sul canale YouTube dell'UMI:
https://youtube.com/playlist?list=PLmySpc-jrtAMq84VH71evyqPc1hl6eEQb
Il prossimo appuntamento è per lunedì 7 aprile 2025. I relatori saranno
Stefano Favaro (Università di Torino) e Mario Beraha (Università di Milano
Bicocca) che parleranno di:
*Il modello di Ewens-Pitman per partizioni aleatorie e la sua (naturale)
estensione alle allocazioni aleatorie*
con il seguente orario:
16:00 Primo seminario
16:30 Pausa e discussione
16:45 Secondo seminario
17:15 Conclusione e discussione
Trovate di seguito il riassunto. I seminari verranno trasmessi via Zoom al
seguente link:
https://unitn.zoom.us/j/87150580430
ID riunione: 871 5058 0430
Codice d’accesso: 591823
Vi aspettiamo numerosi!
Alberto Chiarini e Sonia Mazzucchi
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
RELATORI: Stefano Favaro (Università di Torino) e Mario Beraha (Università
di Milano Bicocca)
TITOLO: Il modello di Ewens-Pitman per partizioni aleatorie e la sua
(naturale) estensione alle allocazioni aleatorie
RIASSUNTO: Nella prima parte del seminario verrà introdotto il modello di
Ewens-Pitman per partizioni aleatorie, presentandone una caratterizzazione
in termini di sufficienza predittiva nell’ambito della classe dei modelli
di campionamento di specie. Successivamente, verrà offerta una panoramica
sui principali teoremi limite relativi al numero di blocchi e blocchi con
molteplicità della partizione di Ewens-Pitman, con particolare attenzione
alle fluttuazioni quasi-certe, ai principi di grandi deviazioni e alle
fluttuazioni Gaussiane. Infine, si illustrerà un’applicazione del modello
di Ewens-Pitman alla soluzione Bayesiana del problema della stima della
“missing mass”, noto come problema di Good-Turing, e della stima del
“unseen”, o problema di Fisher-Efron.
Nella seconda parte del seminario si parlerà di allocazioni aleatorie;
un’allocazione di N oggetti è un multi-insieme di sottoinsiemi non vuoti
degli N oggetti che, al contrario di una partizione, possono non essere
mutuamente esclusivi o esaustivi. Partendo dal modello Indian buffet di
Ghahramani e Griffiths, che costituisce il naturale analogo del modello di
Ewens nel caso di allocazioni, verranno presentati alcuni risultati
sull’analisi Bayesiana di allocazioni aleatorie. In particolare, verranno
discusse caratterizzazioni di sufficienza predittiva per allocazioni
aleatorie, che generalizzano i corrispondenti risultati sui modelli di
campionamento di specie. Due illustrazioni relative al problema delle
“missing features” verranno descritte.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Dear all,
the next OWABI seminar www.warwick.ac.uk/oneworldabc<http://www.warwick.ac.uk/oneworldabc> is quickly approaching, being scheduled on Thursday the 27th March at 11am UK time.
Our next speaker is Meïli Baragatti<https://www.vinifera-euromaster.eu/team/meili-baragatti/> (Université de Montpellier), who will talk about "Approximate Bayesian Computation with Deep Learning and Conformal Prediction", with an abstract reported below.
Abstract: Approximate Bayesian Computation (ABC) methods are commonly used to approximate posterior distributions in models with unknown or computationally intractable likelihoods. Classical ABC methods are based on nearest neighbor type algorithms and rely on the choice of so-called summary statistics, distances between datasets and a tolerance threshold. Recently, methods combining ABC with more complex machine learning algorithms have been proposed to mitigate the impact of these "user-choices''.
In this talk, I will present you the first, to our knowledge, ABC method completely free of summary statistics, distance, and tolerance threshold. Moreover, in contrast with usual generalizations of the ABC method, it associates a confidence interval (having a proper frequentist marginal coverage) with the posterior mean estimation (or other moment-type estimates).
This method, named ABCD-Conformal, uses a neural network with Monte Carlo Dropout to provide an estimation of the posterior mean (or other moment type functionals), and conformal theory to obtain associated confidence sets. I will compare its performances with other ABC methods on several examples, and show you that it is efficient for estimating multidimensional parameters, while being "amortized".
Keywords: Likelihood-free inference · Approximate Bayesian computation · Convolutional neural networks · Dropout · Conformal prediction
Reference: M. Baragatti, B. Cloez, D. M´etivier, I. Sanchez. Approximate bayesian computation with deep learning and conformal prediction. Preprint at ArXiv: 2406.04874, 2024.
This talk is hosted on the OWABI Ms Teams Channel, which is available here https://teams.microsoft.com/l/team/19%3AdhZ_4e_XLNJzCXPAMzTvT6BZ5KShEETkd_w….
The MS Teams link to join Meïli Baragatti's talk is
https://teams.microsoft.com/l/meetup-join/19%3adhZ_4e_XLNJzCXPAMzTvT6BZ5KSh…
Meeting ID: 328 977 159 098
Passcode: zy9vS32A
We're looking forward to seeing you at the next OWABI seminar,
best,
Massimiliano on the behalf of the OWABI Organisers
------
Dr. Massimiliano Tamborrino
Reader (Associate Professor) and WIHEA Fellow
Department of Statistics
University of Warwick
https://warwick.ac.uk/tamborrino
Dear all,
From the 7th until the 11th of April, RoMaDS <https://www.mat.uniroma2.it/~rds/events.php> will host <https://jschmidthieber.personalweb.utwente.nl/> <https://jschmidthieber.personalweb.utwente.nl/>Johannes Schmidt-Hieber <https://jschmidthieber.personalweb.utwente.nl/> (University of Twente) with the mini-course
Statistical theory of deep learning
The schedule is as follows: Mon 14:00-16:30, Wed 14:00-16:30, Fri 14:00-16:30. All lectures will be held in Aula Dal Passo in the Math Department of university of Rome, Tor Vergata.
Here is the program for the three lectures:
Lecture 1. Intro and theory for shallow networks
Perceptron convergence theorem
Universal approximation theorem
Approximation rates for shallow neural networks
Barron spaces
Lecture 2. Theory for deep networks
Advantages of additional hidden layers
Deep ReLU networks
Misclassification error for image deformation models
Lecture 3. Theory of gradient descent in machine learning
Optimization in machine learning
Weight balancing phenomenon
Analysis of dropout
Benign overfitting
Grokking
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…"Tid"%3a"24c5be2a-d764-40c5-9975-82d08ae47d0e"%2c"Oid"%3a"650fc4a8-4cec-4bd2-87bc-90d134074fe6"} <https://teams.microsoft.com/l/meetup-join/19%3arfsL73KX-fw86y1YnXq2nk5VnZFw…>
The seminars are part of the Excellence Project MatMod@TOV.