- Random - Mailing list — Dipartimento di Matematica, UniPI

Complexity72h Call for Tutors
by Mateusz Wilinski 19 Jan '20

19 Jan '20

Dear colleagues, We are glad to announce the *third edition of the Complexity72h workshop*, which will take place at LUISS, Rome, Italy, on *July 1-4 2020*, as pre-event of the *NetSci 2020* Conference. Complexity72h is an interdisciplinary workshop whose aim is to bring together young researchers from different fields of complex systems and complex networks. Participants form teams and carry out projects in a three days' time, i.e. 72 hours. The goal of each team is to upload on the arXiv a report of their work by the end of the event. The previous two editions have been a success: 11 out of 11 projects have become arXiv preprints and new collaborations have been born. Each team will have a tutor that: 1. designs and proposes the project; 2. supervises its execution; 3. provides the necessary knowledge and data. *Do you want to become a Complexity72h tutor?* We are opening a *call for tutors* targeting researchers in complex systems and networks. We are looking for people who wish to propose a stimulating project to a team of highly motivated students and postdocs, and have the stamina to carry it out in 72 hours. But is it really possible to do it in just 72 hours? To succeed, we need: 1. A motivated and multidisciplinary team of resilient researchers; 2. A comfortable research environment and supportive staff; 3. A solid and feasible research project and a tutor who can make it happen. We provide the first two. It is up to you to provide the last point. *Send your project proposal (title and abstract) and short CV to: complexity72h [at] gmail [dot] com* , or get in touch with us as soon as possible if you have any questions. *The call for tutors deadline is February 7th, 2020.* Looking forward to your ideas. Complexity72h Organizers

1 0

7th Workshop on Stochastic Methods in Game Theory
by Marco Scarsini 17 Jan '20

17 Jan '20

The 7th Workshop on Stochastic Methods in Game Theory will take place in Erice July 1-8, 2020. https://sites.google.com/view/erice-smgt2020/the-workshop The workshop will include some tutorials that could be particularly useful to graduate students and young researchers. Some slots are still available for contributors who want to present a poster. ******************************************************* Marco Scarsini Dipartimento di Economia e Finanza Luiss Viale Romania 32 00197 Roma, ITALY URL: http://docenti.luiss.it/scarsini/

1 0

avviso di due seminari a Napoli
by Enrica Pirozzi 17 Jan '20

17 Jan '20

-- AVVISO DI SEMINARI DI PROBABILITÀ E STATISTICA MATEMATICA Title: The risk model with stochastic premiums and a multi-layer dividend strategy by Olena Ragulina Faculty of Mechanics and Mathematics, Taras Shevchenko National University of Kyiv Abstract: The lecture is devoted to a generalization of the risk model with stochastic premiums where dividends are paid according to a multi-layer dividend strategy. First of all, we derive piecewise integro-differential equations for the Gerber-Shiu function and the expected discounted dividend payments until ruin. Next, we concentrate on the detailed investigation of the model in the case of exponentially distributed claim and premium sizes and find explicit formulas for the ruin probability as well as for the expected discounted dividend payments. Moreover, we obtain an exponential bound for the ruin probability under certain conditions and study these conditions for some special distributions of claim and premium sizes. Lastly, numerical illustrations for some multi-layer dividend strategies are presented. -- Title: The first-passage time properties of the Jacobi process and applications to neuronal modeling by Giuseppe D'Onofrio Dipartimento di Matematica "Giuseppe Peano", Università di Torino Abstract: Nonlinear dynamical systems are often affected by different sources of noise and the usual belief is that the presence of noise can hinder or deteriorate the signal transmission in the system. However it has been observed, both in theoretical models and experiments, that random fluctuations can sometimes improve information processing. Mathematical models in neuroscience are one of the most prominent examples of phenomena for which the noise is of primary importance or even a part of the signal itself rather than a source of inefficiency and unpredictability. Our aim is to contribute to the discussion on the role of noise, studying the effects of a multiplicative noise on the performance of single neuron models using an analytical approach on the related first-passage-time problem. We consider a model where the evolution of the neuronal membrane depolarization between two consecutive spikes is described by a Jacobi process. We analyze the spiking activity of the neuron under study through the firing rate and the variability of the output related to the first two moments of the random variable first-passage time and we describe the occurrence of a phenomenon of coherence resonance. In particular we present counterintuitive effects due to the presence of the multiplicative noise and its dependence on the input parameters. Based on joint work with Petr Lansky (Czech Academy of Sciences) and Massimiliano Tamborrino (University of Warwick). I seminari si terranno il 23 Gennaio 2020 ore 15:00 e ore 15:45, rispettivamente, in Aula G terzo livello del Dipartimento di Matematica e Applicazioni, Università di Napoli FEDERICO II, Complesso di Monte Sant'Angelo, Via Cintia, Napoli. -- Enrica Pirozzi Dipartimento di Matematica e Applicazioni Universita' di Napoli FEDERICO II Via Cintia, Monte S.Angelo, 80126, NAPOLI, ITALY Tel. 081 675634 https://www.docenti.unina.it/ENRICA.PIROZZI

1 0

Seminario at Scuola Normale Superiore, Tiziano De Angelis, School of Mathematics, The University of Leeds (January 22, 2020, 11:30)
by Giulia Livieri 17 Jan '20

17 Jan '20

Dear all, On Wednesday, 22 January 2020 — at 11:30 — at the Scuola Normale Superiore (Room: Aula Fermi) Dr Tiziano De Angelis (University of Leeds) will hold the following Seminar: Title Probabilistic results concerning smoothness of the value function and of the free boundary in optimal stopping Abstract I will present probabilistic proofs of some regularity properties for the value function of general optimal stopping problems and for the associated optimal boundaries. In particular this talk focuses on C^1 regularity of the value function and Lipschitz continuity of the optimal boundary. Most of our arguments rely on fundamental concepts from the theory of Markov processes and bridge the probabilistic and the analytical strands of the literature on free boundary problems. I will also illustrate situations in which our work improves or complements known facts from PDE theory. (based on https://epubs.siam.org/doi/pdf/10.1137/17M1113709 <https://epubs.siam.org/doi/pdf/10.1137/17M1113709> and https://arxiv.org/abs/1812.04564 <https://arxiv.org/abs/1812.04564>) Feel free to forward this announcement to your colleagues. Best Giulia Livieri

1 0

Seminar Cuturi @Bocconi
by Giacomo Zanella 16 Jan '20

16 Jan '20

We kindly invite you to the following BIDSA seminar: “Differentiable Ranking and Sorting using Optimal Transport” Marco Cuturi (Google Brain / ENSAE) Friday, January 17, 2020 | 12:30 | Room 3-e4-sr03 (third floor) Bocconi University, Via Roentgen 1, Milan Abstract: We propose in this paper proxy operators for ranking and sorting that are differentiable. To do so, we leverage the fact that sorting can be seen as a particular instance of the optimal transport (OT) problem between two univariate uniform probability measures, the first measure being supported on the family of input values of interest, the second supported on a family of increasing target values (e.g. 1,2,...,n if the input array has n elements). Building upon this link, we propose generalized rank and sort operators by considering arbitrary target measures supported on m values, where m can be smaller than n. We recover differentiable algorithms by adding to this generic OT problem an entropic regularization, and approximate its outputs using Sinkhorn iterations. To illustrate the versatility of these operators, we use the soft-rank operator to propose a new classification training loss that is a differentiable proxy of the 0/1 loss. Using the soft-sort operator, we propose a new differentiable loss for trimmed regression. Speaker: Marco Cuturi joined Google Brain, in Paris, in October 2018. He graduated from ENSAE (2001), ENS Cachan (Master MVA, 2002) and holds a PhD in applied maths obtained in 2005 at Ecole des Mines de Paris. He worked as a post-doctoral researcher at the Institute of Statistical Mathematics, Tokyo, between 11/2005 and 3/2007. He worked in the financial industry between 4/2007 and 9/2008. After working at the ORFE department of Princeton University between 02/2009 and 08/2010 as a lecturer, he was at the Graduate School of Informatics of Kyoto University between 9/2010 and 9/2016 as a tenured associate professor from 10/2013. He then joined ENSAE, the french national school for statistics and economics, in 9/2016, where he still teaches. His recent proposal to solve optimal transport using an entropic regularization has re-ignited interest in optimal transport and Wasserstein distances in the machine learning community. His work has recently focused on applying that loss function to problems involving probability distributions, e.g. topic models / dictionary learning for text and images, parametric inference for generative models, regression with a Wasserstein loss and probabilistic embeddings for words. Best regards, Giacomo Zanella Please note: if you are a guest and you do not have a Bocconi ID Card to access to the Bocconi Buildings, please communicate your participation by sending an email to c.monetti(a)unibocconi.it

1 1

Ernesto De Vito @ Roma Tor Vergata
by Anna Vidotto 16 Jan '20

16 Jan '20

Dear all, I would like to announce the following talk that will be held on Thursday January 23rd 2020, at 4:30 PM, in Aula D’Antoni of the Department of Mathematics, University of Rome Tor Vergata. Speaker: Ernesto De Vito Title: Multi-Scale Vector Quantization with Reconstruction Trees Abstract: The aim of vector quantization is a parsimonious reconstruction of unsupervised data as provided by K-means and geometric multi-resolution analysis, to name a few. In the talk I will present a multi-scale algorithm for vector quantization and study its statistical properties. The proposed approach is inspired by decision trees and is based a family of given partitions, to quickly explore the data in a coarse to fine-multi-scale-fashion. The main technical contribution is an analysis of the expected distortion achieved by the proposed algorithm. Both asymptotic and finite sample results are derived. The presentation is based on a joint work with E. Cecini and L. Rosasco. Kind regards --------- Anna Vidotto PostDoc Researcher Dipartimento di Matematica Università degli Studi di Roma Tor Vergata https://sites.google.com/view/annavidotto

1 0

seminario Djehiche a Milano 27/1/2020
by Marco Alessandro Fuhrman 15 Jan '20

15 Jan '20

Il prof. Boualem Djehiche (KTH Stockholm) terrà un seminario dal titolo On a class of mean-field reflected backward stochastic differential equations and the related obstacle problem. Il seminario è fissato alle ore 10:30 del 27/1/2020 presso il Dipartimento di Matematica dell'Università di Milano (via Saldini 50), in aula C (II piano). Tutti gli interessati sono cordialmente invitati. Un sommario è riportato sotto. Il prof. Djehiche è ospite del Dipartimento per tutta la settimana. Cordialmente, Marco Fuhrman --------------------------- Abstract. In this talk I will review some recent results on the solvability of a class of reflected backward stochastic differential equations (BSDEs) (driven by the Brownian motion) of mean-field type, where the mean-field interaction in terms of the distribution of the Y-component of the solution enters both the driver and the lower obstacle. When the reflected BSDE is driven by an underlying Markov diffusion, it is possible to derive a related obstacle problem in the form of a variational inequality involving differential operators w.r.t. both the space and the probability measure components. -------------------------- <signaturebeforequotedtext></signaturebeforequotedtext><signatureafterquotedtext></signatureafterquotedtext>

1 0

Post-doctoral position in probability - Paris
by Cristina TONINELLI 14 Jan '20

14 Jan '20

Dear friends and colleagues, I am currently advertising a post-doctoral position in Probability at Ceremade, University Paris Dauphine. The position is for two years. The expected starting date is September 2020, though a different date may be arranged. The position is funded by my European project MALIG, whose aim is to develop a mathematical approach to the liquid-glass transition and related phenomena. Main areas of research include interacting particle systems, bootstrap percolation cellular automata and glassy dynamics. The successful candidate will also have the opportunity to collaborate with the probability group of University Roma Tre, in particular with Fabio Martinelli, a key member of the MALIG team. The grant will provide substantial fundings to cover working periods in Rome. There are no teaching duties associated to the position. Candidates can contact me directly for any additional informations. Applications including a CV, a list of publications and a one-page description of research interests and experience should be sent directly to me at toninelli(a)ceremade.dauphine.fr<mailto:toninelli@ceremade.dauphine.fr> Applicants should also arrange for up to three letters of recommendation to be sent to the same address. The deadline for applications is Monday, 3rd February 2020. I would be grateful if you could bring this announcement to the attention of potential candidates and distribute it via local mailing lists. Best wishes, Cristina Toninelli --------------------------------------------------------------------------------------------- Cristina Toninelli Postal Address: Ceremade Univ.Paris Dauphine Place du Marechal de Lattre de Tassigny 75775 Paris Cedex 16 - France Office: B617 --------------------------------------------------------------------------------------------

1 0

de Finetti Risk Seminar - January 2020
by Emanuela Rosazza 14 Jan '20

14 Jan '20

On behalf of the Scientific Committee of the de Finetti Risk Seminars, we are glad to invite you to participate at the following Lecture Quadratic Hedging and Optimization of Option Exercise Policies in Incomplete Markets and Discrete Time Nicola Secomandi Tepper School of Business – Carnegie Mellon University Abstract. This paper extends quadratic hedging from European to Bermudan options in discrete time when markets are incomplete and investigates its use for supporting exercise policy optimization. The key idea is to construct date specific approximate replicating portfolios. Hedging any given exercise policy can be done by solving a collection of stochastic dynamic programs. Optimizing the exercise policy based on the resulting martingale measure requires care. If this measure is risk neutral (RN), the value of an optimal such policy, which can be obtained by augmenting the hedging model with an exercise policy optimization step, is a no arbitrage one. Otherwise this approach must be refined by imposing time consistency on exercise policies, although the value of the resulting exercise policy may not be arbitrage free. Following the common pragmatic strategy of specifying quadratic hedging under an RN measure, e.g., one calibrated to market prices, avoids these issues. In particular, it provides a simple hedging policy with immediate practical applicability and is equivalent to exercise policy optimization under RN valuation, thus complementing it with a consistent hedging policy. A simple numerical example shows that this procedure generates effective hedging policies LOCATION: The seminar will be held on Wednesday, January 15, at 18.00 at room 3-E4-SR03, Bocconi University, Via Rontgen 1, 3rd floor, Milano. Scientific Committee: Prof. Simone Cerreia-Voglio (Univ. Bocconi) Prof. Marco Frittelli (Univ. degli Studi di Milano) Prof. Fabio Maccheroni (Univ. Bocconi) Prof. Marco Maggis (Univ. degli Studi di Milano) Prof. Massimo Marinacci (Univ. Bocconi) Prof. Emanuela Rosazza Gianin (Univ. Milano-Bicocca) ******************************************************************************************* Emanuela Rosazza Gianin Dipartimento di Statistica e Metodi Quantitativi Università di Milano-Bicocca Edificio U7 – 4° Piano Via Bicocca degli Arcimboldi, 8 20126 Milano Tel. 02 64483208 Fax. 02 64483105 e-mail: emanuela.rosazza1(a)unimib.it *******************************************************************************************

1 0

Seminar Announcement: M. Glanzer (univie) at Polimi
by Carlo Sgarra 14 Jan '20

14 Jan '20

On Monday, January 21, at 11:00 o'clock, in the Seminar Room located at the third floor of the MATHEMATICS Department ( POLITECNICO di Milano) MARTIN GLANZER of the University of Vienna will give a talk on the following subject: Stochastic Optimization with Multiple Time Scales ( Joint work with G. Pflug) All interested people are kindly invited to participate. ABSTRACT Real-world multistage stochastic optimization problems are often characterized by the fact that the decision maker may take actions only at specific points in time, even if relevant data can be observed much more frequently. In such a case there are not only multiple decision stages present but also several observation periods between consecutive decisions, where profits/costs occur contingent on the stochastic evolution of some uncertainty factors. We present a tailor-made modeling framework for such problems, which allows for a computationally efficient solution. We first establish new results related to the approximation of (Markovian) stochastic processes by scenario lattices. In a second step, we incorporate the multiscale feature by leveraging the theory of stochastic bridge processes. The ingredients to our proposed modeling framework are elaborated explicitly for various popular examples, including both diffusion and jump models. In particular, we present new results related to the simulation of compound Poisson bridges. Finally, we discuss a valuation problem of a thermal power plant, where implementing our multiscale modeling framework turned out to be particularly convenient. If time permits, we incorporate model ambiguity into the power plant valuation problem and show some numerical results.

1 0