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1.12.2020: Workshop dedicated to the memory of Professor Yuriy Kozachenko
by Luisa Beghin 18 Nov '20

18 Nov '20

Ricevo e inoltro Cordiali saluti. Luisa Beghin We would like to announce the International Workshop "Modern Trends in Probability Theory and Mathematical Statistics III" dedicated to the memory of Professor Yuriy Kozachenko (1.12.1940–5.05.2020). The Workshop will be held on 1 December 2020 from 14:00 to 19:00 Kyiv time (UTC/GMT + 2). The Workshop is organized by the Department of Probability, Statistics and Actuarial Mathematics of Taras Shevchenko National University of Kyiv. Invited Speakers: Giulia Di Nunno (Norway), Rita Giuliano-Antonini (Italy), Alexander Ivanov (Ukraine), Nikolai Leonenko (UK), Andriy Olenko (Australia), Enzo Orsingher (Italy), Vladimir Piterbarg (Russian Federation), Lyudmyla Sakhno (Ukraine), Tommi Sottinen (Finland), Andrei Volodin (Canada). The Workshop will be conducted virtually via Zoom meeting. We invite you to join the Workshop. Please find the program and connection details on the website http://probability.univ.kiev.ua/moderntrends3/ We kindly ask you to share this information among your colleagues, if you find this appropriate. Thank you. Best regards, organizers of the Workshop Prof. Yuliya Mishura Dr. Lyudmyla Sakhno -- Taras Shevchenko National University of Kyiv Department of Probability Theory, Statistics and Actuarial Mathematics 64/13, Volodymyrska St., 01601 Kyiv, Ukraine Tel/fax: (+380-44) 259-03-92 *************************************************************** Luisa Beghin Dipartimento di Scienze Statistiche Fac. Ingegneria dell'Informazione, Informatica e Statistica "SAPIENZA" Università di Roma Piazzale Aldo Moro 5, 00185 Roma T (+39) 06 49910543 F (+39) 06 4959241 https://sites.google.com/site/luisabeghin/ ***************************************************************** -- ________________________________________________________ Le informazioni contenute in questo messaggio di posta elettronica sono strettamente riservate e indirizzate esclusivamente al destinatario. Si prega di non leggere, fare copia, inoltrare a terzi o conservare tale messaggio se non si è il legittimo destinatario dello stesso. Qualora tale messaggio sia stato ricevuto per errore, si prega di restituirlo al mittente e di cancellarlo permanentemente dal proprio computer. The information contained in this e mail message is strictly confidential and intended for the use of the addressee only. If you are not the intended recipient, please do not read, copy, forward or store it on your computer. If you have received the message in error, please forward it back to the sender and delete it permanently from your computer system. --

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Tenure-Track Assistant Professor in Probability - TU Eindhoven
by Pietro Caputo 18 Nov '20

18 Nov '20

Ricevo e inoltro: ------------------- *Tenure-Track Assistant Professor in Probability* The Statistics, Probability and Operations Research (SPOR) cluster of the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) invites applications for a full-time tenure-track position in the area of Probability. For details, see https://jobs.tue.nl/en/vacancy/tenuretrack-assistant-professor-in-probabili…

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Padova Online Seminar by Alessandro Zocca (Vrije Universiteit Amsterdam) [Friday, Nov. 27 at 11.30]
by alessandra bianchi 17 Nov '20

17 Nov '20

Dear Colleagues, We would like to invite you to the following Probability seminar that will take place on November 27 at 11.30 by the zoom platform. ________________________________________________________ Speaker: Alessandro Zocca (Vrije Universiteit Amsterdam) Title: Power grids as stochastic networks: emergent failures and mitigation strategies 27 NOVEMBER (Friday) - 11:30 zoom link: TBA (available on the webpage https://www.math.unipd.it/~bianchi/seminari/ ) Abstract: Power grids are one of the most complex and critical networks in modern-day society, which we expect to function reliably at all times. The increasing adoption of renewable energy sources such as solar panels and wind turbines, introduces a massive amount of uncertainty into power grids, due to their intrinsically intermittent and highly variable nature. In this talk I will give an overview of my current research, which aims to develop new mathematical tools to analyze power grids and their performance in the presence of uncertainty. Stochastic fluctuations of the power injections affect line flows and phase angle frequencies, and, when amplified by correlations and network effects, they can cause failures and possibly blackouts. Large deviations techniques and ad-hoc MCMC methods allow us to better understand how these emergent failures occur and to estimate their likelihood. A peculiar feature of cascading failures in power grids is that they propagate nonlocally, making the control and mitigation of these failures extremely hard. I will illustrate a novel strategy we devise using tools from graph theory, spectral clustering, and optimization to mitigate the impact of line failures and their non-local propagation. -- Alessandra Bianchi Dip. di Matematica Università di Padova Via Trieste, 63 - 35121 Padova, Italy phone: +39 049 827 14 06 fax: +39 049 827 14 28 e-mail: bianchi(a)math.unipd.it http://www.math.unipd.it/~bianchi/

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Six-year PhD position at TU Delft
by Elena Pulvirenti 16 Nov '20

16 Nov '20

Dear all, the Institute of Applied Mathematics at *TU Delft* invites applications for a *Six-year PhD position in Applied Probability and Mathematical Physics*. We are looking for a highly motivated candidate to work on the project *“Statistical mechanics problems on random graphs”* in a joint collaboration under the supervision of Dr. J.L.A. Dubbeldam, Associate professor in the *Mathematical Physics* group and Dr. E. Pulvirenti, Assistant professor in the *Applied Probability* group of Delft Institute of Applied Mathematics (DIAM). The research work for the future PhD candidate focuses on metastability for spins models on random graphs, both from the perspective of theoretical probability and numerical simulations. In addition to the research work, the student is expected to teach (40% of the work load). This position is meant for a candidate who also wants to acquire teaching skills and contribute to the educational program of TU Delft. Therefore the position is for 6 years. See https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details/… for more details. For information about this vacancy, you can contact both J.L.A. Dubbeldam, email: JLADubbeldam(a)tudelft.nl, and E. Pulvirenti, email: E.Pulvirenti(a)tudelft.nl. To apply for this vacancy, please provide *before 12/12/2020*: - a detailed CV (optional: including papers you have submitted / published) - a list of courses taken and grades obtained - a copy of your Master's thesis (or a draft if not yet submitted) - contact information for 2-3 references - motivation letter (explaining why you would make an excellent candidate for this position) Best regards, Elena Pulvirenti

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I: Assegni di ricerca SNS
by Massimo Campanino 16 Nov '20

16 Nov '20

________________________________ Da: Giovanni Dore <giovanni.dore(a)unibo.it> Inviato: lunedì 16 novembre 2020 12:54 A: Dipartimento di Matematica — docenti di struttura e sottostrutture <mat.docenti.all(a)unibo.it> Oggetto: Assegni di ricerca SNS Cari colleghi, comunico che la Scuola Normale Superiore ha bandito 5 assegni di ricerca in ambito matematico. Il bando è disponibile all’indirizzo https://amministrazionetrasparente.sns.it/bando/assegni-di-ricerca-denomina… Cordiali saluti Giovanni Dore

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PhD in Statistics & Computer Science @Bocconi - call for applications
by Antonio Lijoi 16 Nov '20

16 Nov '20

******************* PhD in Statistics and Computer Science - a.y. 2021-2022 Call for applications for PhD student positions ******************* The Bocconi PhD School provides 7 scholarships for the PhD in Statistics and Computer Science, and a position with tuition waiver. * Scholarship amount * 20.280 euro per annum in the 1st and 2nd year 15.343 euro per annum in the 3rd and 4th year Further funding is available through teaching and research assistantship. Visit www.unibocconi.eu/admissionphd for detailed information. ** Applications are due by February 1, 2021 ** Within the PhD School at Bocconi University, the four-year PhD program in Statistics and Computer Science is a high profile and rigorous doctoral program that develops strong mathematical, statistical, computational and programming backgrounds. The curriculum is structured into two tracks: Statistics and Computer science. The first year includes courses that are compulsory for all enrolled PhD students. The second-year features track-specific and elective courses that provide students with a more specialized competence and focus on topics that may be the object of the doctoral dissertation. Dedicated mentorship is offered to students throughout their time at Bocconi. Multidisciplinary interchange with other graduate programs in Bocconi’s PhD School, as well as research experience abroad, are also encouraged. The Faculty includes internationally acknowledged top researchers in Statistics, Computer Science, Decision Theory, Statistical Physics and Machine Learning. The program also benefits from contributions of authoritative visiting professors who deliver short monographic courses. Highly qualified and motivated students with M.Sc. degrees in in Statistics, Mathematics, Computer Science, Economics, Physics, Engineering and related areas, as well as other quantitatively-oriented fields, are encouraged to apply for admission. Applicants should hold, or be on their way to hold, a graduate degree or equivalent. For further information about the PhD program in Statistics and Computer Science at Bocconi, visit www.unibocconi.eu/phdstatscompscience and feel free to contact: Antonio Lijoi (antonio.lijoi(a)unibocconi.it) Angela Baldassarre, PhD administrative assistant (angela.baldassarre(a)unibocconi.it) ------ Antonio Lijoi Bocconi University http://mypage.unibocconi.eu/antoniolijoi/

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Fwd: 3 postdoctoral positions in Mathematics, Computer Science and interactions in Lyon & Saint-Étienne: 2021 campaign Labex Milyon
by Pietro Caputo 14 Nov '20

14 Nov '20

Ricevo e inoltro: ---------- Forwarded message --------- From: sabot(a)math.univ-lyon1.fr <sabot(a)math.univ-lyon1.fr> Date: Fri, Nov 13, 2020, 20:02 Subject: 3 postdoctoral positions in Mathematics, Computer Science and interactions in Lyon & Saint-Étienne: 2021 campaign Labex Milyon Dear Colleagues, Could you please forward this message to interested colleagues and potential candidates (sorry for the inconvenience if you already received it) Best regards, Christophe Sabot Responsible of the Labex Milyon ----------------------------------------------------------------------------------------------------------------------------- The Excellence Laboratory Milyon <https://milyon.universite-lyon.fr/labex-milyon-mathematics-and-theoretical-…> (Labex Milyon) opens the 2021 campaign of postdoctoral researchers in Lyon--Saint-Etienne in Mathematics, Computer Science and their interactions (including some aspects of theoretical physics). *Milyon offers three postdoctoral positions of two years* with no teaching load for the period 2021–2023. The application is open to all research areas of the labex Milyon (see here <https://milyon.universite-lyon.fr/about-research-126697.kjsp?RH=EN-MILYON-9…> ). More information on the link below: https://milyon.universite-lyon.fr/postdoctoral-positions-2021-2023--130160.… Deadline for applications: January 6th 2021

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Webinar of François Caron @ Unimib
by Federico Camerlenghi 13 Nov '20

13 Nov '20

Dear all, We are glad to announce the next DEMS webinar: Wednesday, 18th November 2020, time 13.00 (CET). link to attend: https://unimib.webex.com/unimib/onstage/g.php?MTID=eadc0aefcf2b20a4d5b65dfc… The speaker is *François Caron*, Department of Statistics, University of Oxford (UK). ******************************************************* *TITLE*. *A unified construction for series representations and finite approximations of completely random measures* *ABSTRACT*. Infinite-activity completely random measures (CRMs) have become important building blocks of complex Bayesian nonparametric models. They have been successfully used in various applications such as clustering, density estimation, latent feature models, survival analysis or network science. Popular infinite-activity CRMs include the (generalized) gamma process and the (stable) beta process. However, except in some specific cases, exact simulation or scalable inference with these models is challenging and finite-dimensional approximations are often considered. In this work, we propose a general and unified framework to derive both series representations and finite-dimensional approximations of CRMs. Our framework can be seen as a generalization of constructions based on size-biased sampling of Poisson point process [Perman et al., 1992]. It includes as special cases several known series representations and finite approximations as well as novel ones. In particular, we show that one can get novel series representations for the generalized gamma process and the stable beta process. We show how these constructions can be used to derive novel algorithms for posterior inference, including a generalization of the slice sampler for normalized CRMs mixture models introduced by Griffin and Walker [2011]. We also provide some analysis of the truncation error. Joint work with Juho Lee and Xenia Miscouridou https://arxiv.org/abs/1905.10733 *Details to attend the webinar.* Event number (access code): 174 366 0917 Event password: 18112020 Wednesday, November 18, 2020 1:00 pm, Europe Time (Rome, GMT+01:00) Event address for attendees: https://unimib.webex.com/unimib/onstage/g.php?MTID=eadc0aefcf2b20a4d5b65dfc… ******************************************************* The webinar is organized by the Department of Economics, Management and Statistics (DEMS) of the University of Milano - Bicocca. -- Federico Camerlenghi Assistant Professor RTDb Department of Economics, Management and Statistics University of Milano Bicocca, Milano, Italy. web-page: https://www.unimib.it/federico-camerlenghi

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BANDO RTDA Mat/06 - Dipartimento Scienze Statistiche - Sapienza Università di Roma
by Luisa Beghin 13 Nov '20

13 Nov '20

Cari tutti, è stato pubblicato il bando relativo ad una posizione di ricercatore a tempo determinato di tipo A, presso il Dipartimento di Scienze Statistiche della Sapienza di Roma (con scadenza 3-12-2020). Bando RTDA/03/2020 Prot. n. 1240/2020 del 3.11.2020 - G.U. n. 86 del 3.11.2020 al seguente link: https://web.uniroma1.it/trasparenza/dettaglio_bando/165882 Cordiali saluti. Luisa Beghin *************************************************************** Luisa Beghin Dipartimento di Scienze Statistiche Fac. Ingegneria dell'Informazione, Informatica e Statistica "SAPIENZA" Università di Roma Piazzale Aldo Moro 5, 00185 Roma T (+39) 06 49910543 F (+39) 06 4959241 https://sites.google.com/site/luisabeghin/ ***************************************************************** -- ________________________________________________________ Le informazioni contenute in questo messaggio di posta elettronica sono strettamente riservate e indirizzate esclusivamente al destinatario. Si prega di non leggere, fare copia, inoltrare a terzi o conservare tale messaggio se non si è il legittimo destinatario dello stesso. Qualora tale messaggio sia stato ricevuto per errore, si prega di restituirlo al mittente e di cancellarlo permanentemente dal proprio computer. The information contained in this e mail message is strictly confidential and intended for the use of the addressee only. If you are not the intended recipient, please do not read, copy, forward or store it on your computer. If you have received the message in error, please forward it back to the sender and delete it permanently from your computer system. --

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Webinar DIDONG LI
by Matteo Ruggiero 13 Nov '20

13 Nov '20

WEBINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Joint initiative with MIDAS COMPLEX MODELING RESEARCH NETWORK <http://midas.mat.uc.cl/network> Venerdi 20 Novembre 2020, alle ore 17:00, si terrà il seguente webinar: ------------------------------------------------ Speaker: Didong Li (Princeton and UCLA) Title: Learning & Exploiting Low-Dimensional Structure in High-Dimensional Data Abstract: Data lying in a high-dimensional ambient space are commonly thought to have a much lower intrinsic dimension. In particular, the data may be concentrated near a lower dimensional subspace or manifold. There is an immense literature focused on approximating the unknown subspace and the unknown density, and exploiting such approximations in clustering, data compression, and building of predictive models. Most of the literature relies on approximating subspaces and densities using a locally linear, and potentially multi-scale, dictionary with Gaussian kernels. In this talk, we propose a simple and general alternative, which instead uses pieces of spheres, or spherelets, to locally approximate the unknown subspace. I will also introduce a curved kernel called the the Fisher–Gaussian (FG) kernel which outperforms multivariate Gaussians in many cases. Theory is developed showing that spherelets can produce lower covering numbers and mean square errors for many manifolds, as well as the posterior consistency of the Dirichlet process mixture of FG kernels. Results relative to state-of-the-art competitors show gains in ability to accurately approximate the subspace and the density with fewer components and parameters. Time permitting, I will also present some applications of spherelets, including classification, geodesic distance estimation and clustering. ------------------------------------------------ Join Zoom Meeting https://us02web.zoom.us/j/81832398725?pwd=QUl5eXNIM0xFSXNjTG9IaFZkL0lCQT09 <https://www.google.com/url?q=https%3A%2F%2Fus02web.zoom.us%2Fj%2F8183239872…> Meeting ID: 818 3239 8725 Passcode: 768768 Il webinar è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats <http://www.carloalberto.org/stats> nell’ambito del Complex Data Modeling Research Network midas.mat.uc.cl/network <http://midas.mat.uc.cl/network> in collaborazione con il Collegio Carlo Alberto. Cordiali saluti Matteo Ruggiero --- Matteo Ruggiero University of Torino and Collegio Carlo Alberto www.matteoruggiero.it

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