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Posto RTDB mat/06 alla Sapienza
by Faggionato, Alessandra 16 Sep '19

16 Sep '19

Buongiorno, segnalo che e` uscito il bando per un posto da Ricercatore di Tipo B Mat/06 presso il Dipartimento di Matematica all'Universita' La Sapienza: https://web.uniroma1.it/trasparenza/dettaglio_bando/145453 Vi pregherei di diffondere la notizia tra i possibili interessati. Grazie Saluti, Alessandra -- ************************************************* Prof. Alessandra Faggionato http://www1.mat.uniroma1.it/~faggionato/ Department of Mathematics University "La Sapienza" Piazzale Aldo Moro, 5 00185 - Rome Office 5, Phone (0039) 06 49913252 *************************************************

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Job offer - PhD / PostDoc in Probability in Hildesheim (Germany)
by Sebastian Mentemeier 16 Sep '19

16 Sep '19

Dear colleagues, there is a new group in Probability at the University of Hildesheim (Germany) looking for PhD students and/or Post-Docs with research interests preferably in the field of branching processes, time series analysis or spatial stochastics. Up to two positions (100 %, TV-L 13) can be filled. The position is with teaching obligations. Applicants should be able to teach math in German after their first year. Applicants who finish their Master thesis during this winter term are also welcome. Please contact me for further information. The detailed job offer can be found here (deadline will be extended until October, 7th): https://www.uni-hildesheim.de/stellenmarkt/stellenanzeige/artikel/2019166-w… With best regards, Sebastian Mentemeier -- Prof. Dr. Sebastian Mentemeier Institut für Mathematik Fachbereich 10, Mathematik und Naturwissenschaften Universitaet Kassel Heinrich-Plett-Str. 40, D-34132 Kassel Tel: +49 561 804-4587 E-mail: mentemeier(a)mathematik.uni-kassel.de

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Corso STATISTICAL LEARNING AND BIG DATA
by Andrea Ongaro 16 Sep '19

16 Sep '19

University of Milano-Bicocca Department of Economics, Management and Statistics Phd Programme in Economics and Statistics ***************************************************************************** Si comunica che il Prof. Saharon Rosset, della Tel Aviv University, terrà, nell'ambito delle attività del Dottorato di Ricerca in Economia e Statistica dell'Università degli Studi di Milano-Bicocca, un corso dal titolo: STATISTICAL LEARNING AND BIG DATA http://www.tau.ac.il/~saharon/StatLearn-Milan.html DOCENTE: Saharon Rosset è Professore di Statistica all'Università di Tel Aviv. I suoi interessi di ricerca riguardano statistical learning, data mining e statistical genetics. Prima del suo incarico a Tel Aviv, ha conseguito il dottorato di ricerca presso la Stanford University nel 2003 sotto la supervisione dei Professori Jerome Friedman e Trevor Hastie. I suoi lavori sono stati pubblicati nelle più prestigiose riviste di statistica e machine learning e ha vinto la KDD cup, una delle più prestigiose competizioni di data mining, 4 volte. https://m.tau.ac.il/~saharon/ PERIODO: 7-18 Ottobre 2019 Il corso ha la durata di 28 ore. Le lezioni avranno inizio lunedì 7 ottobre 2019 e proseguiranno fino a venerdì 18, con il seguente orario: - lunedì-venerdì ore 14:30-17:00 - venerdì ore 17:00-18:30 ISCRIZIONE AL CORSO: dal 16 al 23 Settembre 2019 (vedi allegato) *Per maggiori dettagli (docente, programma, prerequisiti, iscrizione), si veda la locandina in allegato. * Un cordiale saluto, Andrea Ongaro

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Seminar Dunson @BIDSA, Bocconi
by Giacomo Zanella 16 Sep '19

16 Sep '19

We kindly invite you to the following BIDSA seminar: “Learning and exploiting low-dimensional structure in high-dimensional data” David Dunson (Duke University) September 19, 2019 | 12:30 | Room AS03 Bocconi University, Via Roentgen 1, underground floor Abstract: This talk will focus on the problem of learning low-dimensional geometric structure in high-dimensional data. We allow the lower-dimensional subspace to be non-linear. There are a variety of algorithms available for "manifold learning" and non-linear dimensionality reduction, mostly relying on locally linear approximations and not providing a likelihood-based approach for inferences. We propose a new class of simple geometric dictionaries for characterizing the subspace, along with a simple optimization algorithm and a model-based approach to inference. We provide strong theory support, in term of tight bounds on covering numbers, showing advantages of our approach relative to local linear dictionaries. These advantages are shown to carry over to practical performance in a variety of settings including manifold learning, manifold de-noising, data visualization (providing a competitor to the popular tSNE), classification (providing a competitor to deep neural networks that requires fewer training examples), and geodesic distance estimation. We additionally provide a Bayesian nonparametric methodology for inference, using a new class of kernels, which is shown to outperform current methods, such as mixtures of multivariate Gaussians. Speaker: David Dunson is Arts and Sciences Distinguished Professor of Statistical Science and Mathematics at Duke University. He is known for his broad spanning contributions to statistical methodology, with a particular focus on novel modeling frameworks and Bayesian approaches that are motivated by complex and high-dimensional data collected in the sciences. This includes latent factor, dimensionality reduction, nonparametric and machine learning methodology. Primary areas of application include neurosciences and brain network modeling, environmental health, ecology, and human fertility among others. He is a fellow of the ASA, IMS and ISBA and has won numerous awards, including most notably the 2010 COPSS President’s Award. His work is very widely cited and he has an H-index over 70 on Google Scholar. Best regards, Giacomo Zanella

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VERA workshop: MACHINE LEARNING FOR FINANCE in Venice
by Marco Corazza 16 Sep '19

16 Sep '19

kind All, on *October 3*, *2019* the following *VERA workshop* will be held: *MACHINE LEARNING FOR FINANCE*. the workshop will be in *Meeting Room 1* of the *Department of Economics* of the *Ca' Foscari University of Venice* (San Giobbe, Cannaregio 873 - 30121 Venezia, Italy). a tentative program is on *https://www.unive.it/data/agenda/3/32112 <https://www.unive.it/data/agenda/3/32112>*. the attendance is free, but for organizational and space reasons, it is necessary to communicate the participation to: *corazza(a)unive.it <corazza(a)unive.it>*. best regards, Marco Corazza -- Nota automatica aggiunta dal sistema di posta.

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Due assegni di ricerca biennali nell'area 01
by Elvira Di Nardo 14 Sep '19

14 Sep '19

Con preghiera di diffusione a tutti gli interessati. *Bando per il conferimento di Assegni di ricerca - XXII Tornata.* Si segnala l'uscita di un bando per due assegni di ricerca biennali nell'area 01. La ricerca si propone lo studio di nuove problematiche attuali della Matematica (applicata e pura), con particolare riferimento a quelle elencate nel progetto scientifico del Dipartimento di Matematica dell'Università di Torino: http://www.dipmatematica.unito.it/do/home.pl/View?doc=dip_prog_scien.html I settori scientifico-disciplinari interessati sono tutti quelli dell'Area 01. Le tematiche di ricerca attive per il SSD MAT/06 sono reperibili http://www.dipmatematica.unito.it/do/gruppi.pl/Show?_id=2oge Le domande di ammissione alla selezione di cui al bando (n. di rep. 3465 del 10/09/2019 ) pubblicato sul sito dell’Università di Torino all’Albo ufficiale di Ateneo https://webapps.unito.it/albo_ateneo/ devono essere presentate ESCLUSIVAMENTE utilizzando la procedura on line: https://pica.cineca.it/unito/ La presentazione delle domande di partecipazione dovrà essere perfezionata e conclusa improrogabilmente entro le ore *13.00 (ora di Roma) del 1° Ottobre 2019.* Cordiali saluti -- %------------------------------------------------------- Elvira Di Nardo Dept. Mathematics "G. Peano" University of Torino Via Carlo Alberto 10 10123 Torino, Italia tel. +39 0116702862 fax +39 0116702878 http://www.elviradinardo.it %-------------------------------------------------------

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Concorso RTD.B - UPO (scadenza 22/09/2019)
by enea giuseppe bongiorno 12 Sep '19

12 Sep '19

*Concorso RTDB 13/D1 - SECS-S/01 (Statistica)* *Scadenza: 22 settembre 2019* *Università del Piemonte Orientale* Cari colleghi, con la presente si ricorda che è in scadenza il bando per un posto di ricercatore a tempo determinato, lettera B, per il settore concorsuale 13/D1 (Statistica), settore scientifico disciplinare SECS-S/01 (Statistica) presso il Dipartimento di Studi per l'Economia e l'Impresa (DiSEI) dell'Università del Piemonte Orientale. Il bando è disponibile alla pagina: https://www.uniupo.it/alta-formazione-aziende-lavoro/concorsi/concorsi-il-p… Si prega di diffondere la comunicazione tra i potenziali interessati. Cordiali saluti, -- ------ Enea Bongiorno, PhD Università degli Studi del Piemonte Orientale Via Perrone 18, 28100, Novara, Italia Tel: +390321375317 <0321%20375317> e-mail: enea.bongiorno(a)uniupo.it

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seminario di Barbara Martinucci
by Enrica Pirozzi 09 Sep '19

09 Sep '19

AVVISO di SEMINARIO Alcuni risultati sul processo del telegrafo in presenza di barriere elastiche Dr. Barbara Martinucci Dipartimento di Matematica, Università degli Studi di Salerno (Abstract in allegato) Il seminario si terrà il giorno 10 Settembre 2019 ore 12:00 nell?Aula D al primo livello del Dipartimento 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

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Seminar Guindani @Bocconi
by Giacomo Zanella 06 Sep '19

06 Sep '19

We are glad to announce the first DEC Statistics Seminar of the Fall 2019 series: Thursday, September 12 12:30 Meeting room 3-e4-sr03, Bocconi University, Via Roentgen 1, 3rd floor Michele Guindani (University of California, Irvine) Title: Bayesian Approaches to Dynamic Model Selection Abstract: In many applications, investigators monitor processes that vary in space and time, with the goal of identifying temporally persistent and spatially localized departures from a baseline or ``normal" behavior. In this talk, I will first discuss a principled Bayesian approach for estimating time-varying functional connectivity networks from brain fMRI data. Dynamic functional connectivity, i.e., the study of how interactions among brain regions change dynamically over the course of an fMRI experiment, has recently received wide interest in the neuroimaging literature. Our method utilizes a hidden Markov model for classification of latent neurological states, achieving an estimation of the connectivity networks in an integrated framework that borrows strength over the entire time course of the experiment. Furthermore, we assume that the graph structures, which define the connectivity states at each time point, are related within a super-graph, to encourage the selection of the same edges among related graphs. Then, I will propose a Bayesian nonparametric model selection approach with an application to the monitoring of pneumonia and influenza (P&I) mortality, to detect influenza outbreaks in the continental United States. More specifically, we introduce a zero-inflated conditionally identically distributed species sampling prior which allows borrowing information across time and to assign data to clusters associated to either a null or an alternate process. Spatial dependences are accounted for by means of a Markov random field prior, which allows informing the selection based on inferences conducted at nearby locations. We show how the proposed modeling framework performs in an application to the P&I mortality data and in a simulation study and compare with common threshold methods for detecting outbreaks over time, with more recent Markov switching based models, and with other Bayesian nonparametric priors that do not take into account spatio-temporal dependence. Kind regards, Giacomo Zanella The DEC statistics seminars schedule is available at http://www.unibocconi.eu/statseminar 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 arianna.colombo(a)unibocconi.it *************************************************** Giacomo Zanella Assistant Professor - Statistics DEC - Department of Decision Sciences Bocconi University

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Fwd: TOFFEe workshop @IMT, Lucca, 24-25 October
by Irene Crimaldi 05 Sep '19

05 Sep '19

Dear all, we kindly ask you to advertise the 1st TOFFEe workshop and contribute with your latest results on methodologies for fighting disinformation. TOFFEe - https://toffee.imtlucca.it/ - is an interdisciplinary research project funded by IMT School For Advanced Studies Lucca. The project ambition is to overcome some of the limitations of existing social platforms, which often dedicate little attention to trustworthy interactions among peers and to reliability of information. The aim of the project is to increase people's confidence on the data they get and who they follow, while minimising the risk of exposure to fake information and malicious actions. As part of the dissemination activities of the project, on * October 24th and 25th*, 2019, we organise an International Workshop where different approaches for fighting fakes will be exposed. You can find all infos at https://toffee.imtlucca.it/. We would be delighted if you could join us. The registration to the workshop is free, just fill the form at https://toffee.imtlucca.it/. We kindly ask you to register before the * 9th of October*. The registration comprehends two coffee breaks and one lunch. Analogously, we would be delighted if you could contribute to the workshop with your latest results. The slot for the contributions last nearly 15 minutes, plus some time for questions. You can send us a 2 pages abstract at the present email address. The deadline for sending the abstract is on the *25th of September*. We will return our decision on the *2nd of October*. Looking forward to meeting you in Lucca in October, we send you our best regards, Rocco De Nicola (project coordinator) Guido Caldarelli Irene Crimaldi Marinella Petrocchi Fabio Saracco

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