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Postdoc position in Geometric Methods for Machine Learning and Deep Learning at RIST
by Luigi Malagò 14 Dec '18

14 Dec '18

=========================================================== *Subject*: Postdoc position in Machine Learning (1 year, renewable up to 2 years) *Institution*: RIST - Romanian Institute of Science and Technology, Cluj-Napoca *Keywords*: Geometry of Latent Spaces, Optimization over Manifolds, Information Geometry, Natural Gradient, Riemannian Geometry *Application deadline*: 10 October 2018 (applicants are encouraged to apply earlier) *Salary*: around 2200 euro net *Official announcement*: http://rist.ro/en/details/news/postdoc-positions-in-deep-learning-and-machi… =========================================================== Dear colleagues, the Romanian Institute of Science and Technology (RIST) has an opening for a postdoc position, in the context of the DeepRiemann project “Riemannian Optimization Methods for Deep Learning”, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 1 year, with possible extensions up to 2 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group https://rist.ro/en/teams.html, which performs research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, using geometric methods based on Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-deep-learning-and-machi… Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, principal investigator of the DeepRiemann project. Application deadline: 10 October 2018 (applicants are encouraged to apply earlier) best regards, Luigi Malagò

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Seminario di Davide Bignamini a Pavia
by Carbone Raffaella 13 Dec '18

13 Dec '18

Cari colleghi, vi annuncio che giovedì 20 dicembre, alle ore 12, nell'aula Beltrami del Dipartimento di Matematica dell'Universita' di Pavia, il Dott. Davide Bignamini (Università di Parma) terrà un seminario dal titolo Enclosures and structure of invariant states for quantum channels di cui segue il sunto. Distinti saluti, Raffaella Carbone Abstract: In my talk I will present some probability properties for quantum channels, and I will show some similarities with the theory of classical Markov chains. At first I will introduce the concepts of reducibility, invariant state and enclosure. After that I will discuss the structure of invariant states related to the possible decompositions in enclosures of the positive recurrent subspace. Finally I will reconsider this result for a particular case of homogeneous open quantum random walks. This talk is based on the contents of my Master's thesis (Tesi di Laurea Magistrale).

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Seminario SESIA
by Matteo Ruggiero 13 Dec '18

13 Dec '18

STATISTICS SEMINARS @ COLLEGIO CARLO ALBERTO Mercoledì 19 Dicembre 2018, alle ore 11:00, presso il nuovo edificio del Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Matteo SESIA (Stanford University) NEW TOOLS FOR REPRODUCIBLE VARIABLE SELECTION WITH KNOCKOFFS Model-X knockoffs [1] is a new statistical framework that allows the scientist to investigate the relationship between a response of interest and hundreds or thousands of explanatory variables. In particular, model-X knockoffs can be used to identify a subset of important variables from a larger pool that could potentially explain a phenomenon under study while rigorously controlling the false discovery rate [2] in very complex statistical models. In this talk we will briefly review the fundamentals of knockoffs and their use in two different scenarios. First, we will discuss about how knockoffs can be used to exploit prior knowledge of genetic variation to obtain a powerful tool for genome-wide association studies [3]. Then, we will see how the information contained in large unsupervised datasets can be harnessed to perform effectively "model-free" variable selection [4]. [1] E. J. Candès, Y. Fan, L. Janson, and J. Lv, "Panning for gold: "model-X" knockoffs for high dimensional controlled variable selection". Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2018. [2] Y. Benjamini and Y. Hochberg, "Controlling the false discovery rate: a practical and powerful approach to multiple testing". Journal of the Royal Statistical Society: Series B (Statistical Methodology), 1995. [3] M. Sesia, C. Sabatti, and E. J. Candès, "Gene hunting with hidden Markov model knockoffs". Biometrika, 2018. [4] Yaniv Romano, Matteo Sesia and Emmanuel Candès, "Deep Knockoffs". arXiv:1811.06687, 2018. ------------------------------------------------ Tutti gli interessati sono invitati a partecipare. Il seminario è organizzato dalla "de Castro" Statistics Initiative (www.carloalberto.org/stats) 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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Fwd: Postdocs in probability or statistics
by Francesco Caravenna 13 Dec '18

13 Dec '18

Ricevo e inoltro. > Da: Christina Goldschmidt <goldschm(a)stats.ox.ac.uk> > Oggetto: Postdocs in probability or statistics > Data: 12 dicembre 2018 09:56:31 CET > > Dear colleagues, > > The Department of Statistics and Lady Margaret Hall, Oxford are currently advertising two postdocs, open to candidates working in probability or statistics. The jobs come with some associated teaching duties and are fixed term positions lasting until 31st March 2021. Please see the advertisement <https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.disp…> for more details and for how to apply. Prospective candidates should feel free to contact me if they have any questions. The deadline for applications is 11th January 2019. > > I would be most grateful if you could forward this message to any suitable candidates. > > Best wishes, > Christina Goldschmidt. > > -- > Christina Goldschmidt | http://www.stats.ox.ac.uk/~goldschm <http://www.stats.ox.ac.uk/~goldschm> > Department of Statistics and Lady Margaret Hall, University of Oxford

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assegno di ricerca
by Sara Pasquali 13 Dec '18

13 Dec '18

Si avvisa che e' stato pubblicato un bando per un assegno di ricerca annuale presso l'istituto IMATI del CNR di Milano, per la seguente tematica: modelli matematici basati su equazioni differenziali, metodi di stima statistica dei parametri, metodi per modelli state-space. Costituiranno titolo preferenziale la capacità di sviluppare in autonomia codici di programma per la simulazione di modelli matematici o per la statistica computazionale o l’esperienza nell’analisi di modelli descritti da equazioni differenziali o la conoscenza di metodologie di controllo. Tutte le informazioni sono disponibili sul bando http://bandi.urp.cnr.it/doc-assegni/documentazione/8430_DOC_IT.pdf Gli interessati possono contattare il Dott. Antonio Pievatolo (antonio.pievatolo(a)mi.imati.cnr.it) o la Dott.ssa Sara Pasquali (sara.pasquali(a)mi.imati.cnr.it) per maggiori informazioni. -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Dr. Sara Pasquali CNR-IMATI Via Bassini, 15 20133 MILANO - ITALY =========== Tel. +39 02 23699525 Fax. +39 02 23699538 e-mail: sara.pasquali(a)mi.imati.cnr.it ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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seminario di Andrea Agazzi al Politecnico di Torino, 18 dicembre
by Enrico Bibbona 12 Dec '18

12 Dec '18

Gentilissimi, con la presente si comunica che martedì 18 dicembre, ore 09:30, presso il Politecnico di Torino, DISMA, Aula Buzano, il Dott. Andrea Agazzi presenterà un seminario dal titolo: “Scaling limits for Stochastic Chemical Reaction Network Dynamics" Questo evento è parte del "Progetto di eccellenza", DISMA - Politecnico di Torino. Maggiori informazioni reperibili nella locandina https://areeweb.polito.it/disma-excellence/allegati/seminario_Agazzi_DISMA.… e sul sito: www.polito.it/disma-excellence/ Cordiali saluti - - - - - - - - - - - - - - - - - - - - - - - - - - - - Dear colleagues, it is our pleasure to invite you to the seminar “Scaling limits for Stochastic Chemical Reaction Network Dynamics" by Dr Andrea Agazzi. The seminar will be held at Politecnico di Torino, DISMA, Aula Buzano, on Tuesday the 18th December 2018 at 09:30. This event is part of "Progetto di eccellenza", DISMA - Politecnico di Torino. Further information available on the flyer https://areeweb.polito.it/disma-excellence/allegati/seminario_Agazzi_DISMA.… and at www.polito.it/disma-excellence/ Best regards, DISMA Politecnico di Torino Dipartimento di eccellenza 2018-2022 Enrico Bibbona Probability, Statistics and Optimization group Department of Mathematical Sciences "G. L Lagrange" Politecnico di Torino

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avviso seminario Mauro Mariani
by Franco Flandoli 12 Dec '18

12 Dec '18

Il giorno lunedì 17 dicembre, alle ore 10:30, in aula Aula Marie Curie Il professor Mauro Mariani (High School of Economics, Moscow) terrà un seminario dal titolo: The low temperature limit of Dirichlet energies Tutti gli interessati sono invitati a partecipare. Franco Flandoli Abstract: Let M be a Riemannian manifold equipped with a reference measure m with density \exp(- V/T) with respect to the volume measure, where V represents a potential and the positive constant T represents the temperature. The Dirichlet energy with reference measure m is a classical functional defined on the space of probability measures on M. I will discuss the variational convergence of such a functional in the limit T \to 0. In particular, if V is not convex, a non-trivial expansion by Gamma-convergence holds under generic hypotheses on V. The results are based on a joint work with G.DiGesu (TU Wien).

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Seminario Stefano Bonaccorsi @ LUISS
by Giovanni Alessandro Zanco 11 Dec '18

11 Dec '18

Dear all, we inform that Professor Stefano Bonaccorsi (Università di Trento) will give a seminar at LUISS University on Tuesday, December the 18th at 10:00 am in Room 205b, Viale Romania 32 with the following title and abstract Title: Some notes on Malliavin calculus, surface integrals and integration by parts formulae in infinite dimensional spaces Abstract: We introduce a basic construction of the Malliavin calculus which unifies some different perspectives (e.g., Bogachev, Da Prato, Lunardi, Nualart). Then we introduce, for suitable functionals of the Brownian motion, the problem of constructing a surface measure (i.e., the restriction of the reference measure on the infinite dimensional Wiener space) on the level sets defined by them. Finally, we give some interpretation of such results in terms of other stochastic processes. Kind regards Giovanni Zanco LUISS Università Guido Carli Department of Economics and Finance V.le Romania 32 00197 Roma

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Free Program on Data Science for Finance and Quantitative Risk/Portfolio Management
by Stefano Herzel 10 Dec '18

10 Dec '18

The Department of Economics and Finance of the University of Rome "Tor Vergata" (DEF) and ARPM - Advanced Risk and Portfolio Management will jointly offer the course ARPM marathon free of charge to PhD students of Italian institutions. The program will run from January 21st 2019 to June 14th 2019. The ARPM Marathon is an online/onsite, advanced master-level, quantitative program, divided in four courses: - Data Science for Finance - Financial Engineering for Investment - Quantitative Risk Management - Quantitative Portfolio Management The program consists of multiple weekly online preparation sessions with theory and practice in the ARPM Lab online, and one weekly onsite meeting at DEF to discuss and share comments and ideas, under the supervision of prof. Alessandro Ramponi, a faculty member of DEF. Participation to the weekly onsite meetings is necessary to remain enrolled in the program. The program is designed to enable students with a solid mathematical background to operate across all functions in banking, insurance and asset management, or to perform advanced applied research. Upon enrollment, students will obtain access to: - ARPM Lab online: theory, case studies, simulation clips, slides, exercises, code (Python and MATLAB), video lectures - Onsite flipped classroom breakout sessions at DES - Private forum for technical Q&A and networking - Homework assignments - Schedule and personal trainer reminding of all upcoming to-do’s Upon completion of any of the four courses, students will attain a Certificate of Completion. Seats are limited: to be considered for enrollment, interested PhD students should send a motivation letter and their resume to info(a)arpm.co by January 7th, 2019 Best regards, Stefano Herzel - Director of M.Sc. Finance in and Banking, University of Rome "Tor Vergata" Attilio Meucci - Founder, ARPM

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PhD position in stochastic analysis at Leeds
by Elena Issoglio 10 Dec '18

10 Dec '18

Dear Colleagues, At the University of Leeds we have a PhD position in stochastic analysis for UK and EU applicants within the framework "Leeds York NERC Doctoral Training Partnership (DTP)". Details are as follows: Topic: Mean field methods for stochastic population dynamics (http://www.nercdtp.leeds.ac.uk/projects/index.php?id=892) Deadline: Monday 7th January 2019 Start Date: October 2019 How to apply: http://www.nercdtp.leeds.ac.uk/how-to-apply/ More info: please contact Elena Issoglio at e.issoglio(a)leeds.ac.uk Please draw this to the attention of potential candidates. With best wishes, Elena Issoglio Dr Elena Issoglio Lecturer in Financial Mathematics Office 11.02, School of Mathematics School of Mathematics, University of Leeds, Leeds, LS2 9JT E: e.issoglio(a)leeds.ac.uk<mailto:e.issoglio@leeds.ac.uk> T: 0113 34 3 4660

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