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Postdocs in Riemannian Manifold Optimization, Deep Learning and Information Geometry at RIST
by Luigi Malagò 03 Nov '16

03 Nov '16

[apologies for cross-posting] The Romanian Institute of Science and Technology (RIST) has an opening for 3 postdoc positions, 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 2 years, with possible extensions up to 4 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, which will be performing research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, including nature-inspired optimization algorithms, from the unifying perspective of Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST, where about 20 new postdoctoral research associates and research software developers will be hired in the next year. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-machine- learning-optimization-deep-learning-and-information-geometry.html # Jobs Description # The three open positions will focus on different and overlapping aspects of the project: 1) Optimization Algorithms over Statistical Manifolds with Applications to Deep Learning The postdoctoral researcher will conduct research on the design and implementation of novel first- and second-order methods for the optimization of functions defined over statistical models, such as exponential families, the Gaussian distribution, and Markov Random Fields. In particular the research will focus on the optimization problem associated to the training of a Neural Network, which will be studied from the perspective of Optimization over Manifolds with non-Euclidean geometries. The postdoctoral candidate will develop optimization algorithms which explicitly take into account the Riemannian and dual-affine Hessian geometries of the search space, given by the Fisher information metric. Such algorithms should be efficient, scalable, largely parallelizable, and suitable for the large scale and big data settings. Keywords: stochastic gradient descent, Riemannian manifolds, dually-flat Hessian geometries, optimization over manifolds, second-order optimization methods, large scale optimization, nature-inspired optimization algorithms 2) Theory of Neural Networks The postdoctoral researcher will contribute towards the definition of a probabilistic and geometric framework for the study of deep Neural Networks aimed at a better understanding of the working mechanisms behind the success of Deep Learning. The analysis is focused towards a better understanding of what enables Deep Learning systems to achieve remarkable successes, and of its limits, in classification and predictive analysis, with a particular focus on the learning task, in order to guide the development of novel algorithms. The research will include the study of the representational power of various Neural Networks topologies, by taking into consideration the impact of hierarchical architectures with respect to the expressiveness of the network; and the analysis of the number of local minima and of saddle points, which appear during the training and which strongly affect convergence of the optimization algorithms, depending on the nature of the network. Keywords: theory of neural networks, deep learning, learning representations, expressive power of neural networks. 3) Information Geometry of dually-flat Hessian Manifolds The postdoctoral researcher will focus on the characterization of first and second-order Riemannian and affine geometries of statistical models, or more in general Hessian manifolds, aimed at the study of optimization methods over statistical manifolds. Neural Networks can be modeled as statistical manifolds, or manifolds of Neural Networks, and the training of the network can be studied as an optimization problem over a non-linear manifold, where the weights of the network are the parameters of the model and thus the variables of the function to be optimized. The purpose of the analysis is to introduce alternative second-order approximations of a function over a statistical manifold, depending on the choice of the connection and thus how parallel transport is implemented, which are at the basis of the design of second-order optimization methods. Keywords: information geometry, geometry of statistical models, natural gradient, dually-flat manifolds, Hessian geometries. # Desired Qualifications # - PhD in machine learning, theoretical computer science, stochastic optimization, statistics, applied mathematics, including fields such as manifold optimization, differential geometry, statistical mechanics, and related fields - Strong publication record - Strong analytical skills, such as problem solving and logical thinking - Enthusiasm to work in a multidisciplinary and international research environment - Good written and oral communication skills in English Knowledge in machine learning is helpful, but not strictly mandatory. Doctoral students close to the competition of their thesis will also be considered. The positions are to start as early as December 2016 or at any agreed later date. Applications will be reviewed as they are received. RIST offers competitive salaries and top-level working conditions. The net salary for these positions will be around 2.000 euro per month, with a possible increase up to 2.200 euro, based on new tax incentives for research and development activities in Romania. Positions are endowed with travel resources. The cost of living in Cluj is significantly lower than in Western Europe or the USA (e.g., it is 1/3 of the cost of living in London, UK). # How to Apply # In order to apply to this position, the candidate should send an email to deepriemann.jobs(a)rist.ro, mentioning in the subject of the email "DeepRiemann Postdoc Application". The email should include among the attachments: - A cover letter - A complete CV with full list of publications - A short research statement (max 3 pages), which describes your research interests and explain why your skills, knowledge and experience makes you a suitable candidate for one or more of the open positions - The pdfs of 2 selected publications - Name and contact information of up to 3 referees, which will be contacted directly by the institute for a reference letter Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, Principal Investigator of the DeepRiemann project. # About the Institute # The Romanian Institute of Science and Technology is a non-governmental, not-for-profit, independent research institute, founded in 2009, with the purpose of offering scientists a place to conduct research in Romania with top working conditions, comparable to those you can find in Western Europe. RIST currently performs research on computational and experimental neuroscience, computational intelligence, machine learning, and dynamical systems. The institute is currently undergoing a phase of significant and sustained growth supported by European and Romanian structural funds, with plans for hiring around 20 new scientists and researchers in the next year. The institute has close contacts with the Babeș-Bolyai University, which is the largest university in Romania, and with the Technical University of Cluj-Napoca. The institute is located in Cluj-Napoca, in the heart of Transylvania, which has been named by Lonely Planet as the top region to visit in 2016. Cluj is a welcoming and innovative city, recently listed as one of the major tech hubs (with a 9% growth per year for IT industry). Cluj has 12 universities, over 70k students every year, and an extremely vibrant startup scene, which has recently named the Silicon Valley of Transylvania. Cluj is Europe's friendliest city for foreigners, according to a study by the UK Office of National Statistics, and Romania is no. 16 in the Internations best expat destinations of 2016. About 1100 French citizens, 800 Italian citizens and 500 German citizens live in Cluj (source). The city has an international airport, only 8km away from the city center, with flights to more than 30 European destinations. More information about Cluj: https://vimeo.com/171864331 https://vimeo.com/166021527 -- Luigi Malagò Principal Investigator Romanian Institute of Science and Technology - RIST Address: Str. Cireşilor 29, 400487 Cluj-Napoca, Romania Homepage: http://www.luigimalago.it Office: +40 364 408794 Mobile: +39 340 6249299

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Annuncio di seminario
by Piccioni, Mauro 03 Nov '16

03 Nov '16

Dipartimento di Matematica, Sapienza Università di Roma Martedì 8 novembre Ore 14:00, Aula di Consiglio Seminario di Probabilità e Statistica Matematica Pham Thi Da Cam, Université de Tours, France The survival probability of a critical multi-type branching process in i.i.d. random environment Abstract: We consider Galton Watson branching processes of unique type and multi-type in fixed and in random environment. The main target is to observe the asymptotic behaviour of the survival probability of the population. In particular, we utilise the generating function method thanks to the recursive structure of the process in deterministic case and condition to the generating function of offspring distribution in random case. Tutti gli interessati sono invitati a partecipare. Per qualsiasi richiesta di informazione scrivere a piccioni(a)mat.uniroma1.it

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Seminario di Cambyse Rouzé a Pavia
by Carbone Raffaella 02 Nov '16

02 Nov '16

Cari colleghi, vi annuncio che martedì 8 novembre, alle ore 15 precise, nell'aula Beltrami del Dipartimento di Matematica dell'Universita' di Pavia, il Dott. Cambyse Rouzé (University of Cambridge) terrà un seminario dal titolo Convergence properties of a quantum diff usion semigroup via concavity of the quantum entropy power di cui segue il sunto. Distinti saluti, Raffaella Carbone Abstract The entropy power, rst de ned by Shannon in his seminal paper, lead to many celebrated results in information theory and probability theory. In 1985, Costa proved that the entropy power of a random variable with added Gaussian noise of linearly increasing variance is concave with respect to . The proof of this result was later simpli ed by Dembo by an argument based on the so-called Blachman-Stam inequality. This result (and the intermediate steps of its proof) led to many applications ranging from contractivity properties of certain Markov semigroups to entropic versions of the Central limit theorem. In this talk I will discuss a recent analogue of this result proved in the context of quantum harmonic analysis on phase space. I will then use this result to bound the time of convergence in relative entropy of a state evolving under a quantum analogue of the heat semigroup. This is joint work with Dr. Nilanjana Datta and Dr. Yan Pautrat. -- Raffaella Carbone, PhD Ricercatore di Probabilità e Statistica Matematica Dipartimento di Matematica dell'Università degli Studi di Pavia

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"5th Conference in Memory of Carlo Giannini" (PROGRAMME) (fwd)
by Tiziano Vargiolu 29 Oct '16

29 Oct '16

From: Urga, Giovanni Sent: 29 October 2016 08:59 To: Subject: "5th Conference in Memory of Carlo Giannini" (PROGRAMME) Dear Colleagues Please find attached the programme of the forthcoming conference in Memory of Carlo Giannini to be held next 25 & 26 November at the University of Bergamo. Please feel free to circulate the flyer. Finally, please do not forget to register using the following link http://www00.unibg.it/formconvegni2/maschera.asp?convegno=3576. Looking forward to seeing you in Bergamo in a few week time. Regards Giovanni **************************************************************** Please use both addresses: giovanni.urga(a)unibg.it and g.urga(a)city.ac.uk **************************************************************** Giovanni Urga Professor of Finance and Econometrics Faculty of Finance Cass Business School 106 Bunhill Row London EC1Y 8TZ (U.K.) Tel.+/44/(0)20/70408698 Fax.+/44/(0)20/70408881 www.cass.city.ac.uk/experts/G.Urga https://sites.google.com/site/urgagiovanni/ Director, Centre for Econometric Analysis (CEA@Cass) http://www.cass.city.ac.uk/cea/index.html Professore di Econometria, Department of Management, Economics and Quantitative Methods, Bergamo University (Italy) http://www00.unibg.it/struttura/strutturasmst.asp?rubrica=1&persona=689&nom e=Giovanni&cognome=Urga&titolo=Prof.

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ARPM job opportunity
by Elisa Appolloni 28 Oct '16

28 Oct '16

Dear all, I am reaching out to you because at ARPM (the company for which I work) we are looking to add new resources for our Advanced Risk and Portfolio Management program. Would you mind circulating the message below to interested and qualified candidates? Thank you, Elisa Appolloni *** *The firm* ARPM – Advanced Risk and Portfolio Management <https://www.arpm.co/> is a privately held research institution, directed by Attilio Meucci, based in New York City with virtual offices world-wide. ARPM’s mission is to set and disseminate the standards for advanced quantitative risk management and portfolio management across the financial industry: asset management, banking, and insurance. *The opportunity * ARPM is looking for a new researcher-in-training for a minimum period of 6 months, indefinitely extensible. The successful candidate will review and code practical case studies and theoretical examples in quantitative finance, contributing to the ARPM Lab <https://www.arpm.co/lab/books.php?action=page&id=14>. The successful candidate will work full-time, remotely, constantly communicating via multi-media with the other members of ARPM. The ARPM researcher-in-training position represents a great opportunity for candidates with strong academic background, who wish to apply to real problems in finance the rigorous, research-oriented approach acquired in their schooling. *The progression* ARPM emphasizes the constant intellectual growth of its resources. For the first 6 months the researcher-in- training will be focused on specific projects. At the end of this period (s)he will conduct a presentation on the topics covered. Then, (s)he will start broadening his/her scope, attending the presentations of their peers and seniors, working on broader projects, and acquiring hands-on- knowledge of all the topics of the ARPM Lab <https://www.arpm.co/lab/books.php?action=page&id=14>. The approximate time required to attain the required level of familiarity with the ARPM Lab <https://www.arpm.co/lab/books.php?action=page&id=14> is: two years for a recent master’s graduate; one year for a recent PhD graduate. When ready, the researcher-in-training will be tested on all such topics with an exam. If successful, (s)he will conclude his/her training period, attaining the title of ARPM researcher. The ARPM researcher will then engage in highly quantitative projects with ARPM clients, becoming a profit center. *The candidate* [image: arrow_20]Master’s degree in mathematics, physics, engineering, computer science, statistics, data science, quantitative economics. [image: arrow_20]PhD in hard sciences or master’s degree in quantitative finance is a plus. [image: arrow_20]Very strong command of foundational mathematics, including multivariate calculus and linear algebra. [image: arrow_20]Good knowledge of statistics and probability. [image: arrow_20]Proficiency in MATLAB, Python, or similar programming languages. [image: arrow_20]Good command of English. *Compensation* Competitive For more information, please visit arpm.co <https://www.arpm.co/> and/or contact us at info(a)arpm.co <info(a)arpm.co?Subject=job%20Post> -- *ARPM <http://www.arpm.co/>** - Advanced Risk and Portfolio Management**®*

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BIDSA Inaugural Conference
by Federico Camerlenghi 24 Oct '16

24 Oct '16

********************************************************** INAUGURAL CONFERENCE BOCCONI INSTITUTE FOR DATA SCIENCE AND ANALYTICS ********************************************************** The Bocconi Institute for Data Science and Analytics (BIDSA) is pleased to announce its inaugural conference that will be held on November 18, 2016, at the Bocconi University in Milano. ** PROGRAM ** 14:30 - Welcome Address by - Gianmario Verona, Rector of the Bocconi University 14:50 - Lectures by - Michael I. Jordan (University of California, Berkeley) - Marc Mézard (École Normale Supérieure) 16:10 - Coffee Break 16:40 - Lectures by - Aldo Rustichini (University of Minnesota) - Riccardo Zecchina (Politecnico di Torino) The event will be held in room N07, Piazza Sraffa 13 (Velodromo). Participation is free but registration by November 5, 2016 is required. The online registration form is available at https://eventi.unibocconi.it/index.php?key=ev2016090138 For any additional information feel free to write to: bidsa(a)unibocconi.it

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Conference "Actuarial Risks in the Solvency II Era: frontiers of mathematics and regulation"
by Sabrina Mulinacci 24 Oct '16

24 Oct '16

Dear Colleagues, we are glad to invite you to the Conference on Actuarial Risks in the Solvency II Era: frontiers of mathematics and regulation that is going to be held in Bologna, November 3-4-5, 2016. The program will include a tutorial directed to students, scholars and practitioners interested in mastering the state of the art of theory. Interested students may earn 3 credits upon attending the conference and providing a written discussion of some the presentations in the conference. On Saturday November 5th, there will be an informal meeting for networking on current research and discussion ofspecial topics for future research. More detailed informations are available at http://www2.stat.unibo.it/actuarial-risk/Home.html? Best Regards Sabrina Mulinacci?

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Eurocast 2017 - deadline approaching
by Antonio Di Crescenzo 24 Oct '16

24 Oct '16

Dear Colleague, we kindly remind that the deadline for the abstract submission is approaching. Workshop "Stochastic Models and Applications to Natural, Social and Technical Systems" of the Sixteenth International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, February 19-24, 2017. An extended two pages abstract must be sent by e-mail to eurocast(a)iuctc.ulpgc.es until October 31, 2016. Selected full final papers for publication will be required before April 30, 2017. Further information is available at the conference web page (<http://eurocast2017.fulp.ulpgc.es/>http://eurocast2017.fulp.ulpgc.es/). Looking forward meeting you at the Workshop. Best regards, Antonio Di Crescenzo and Amelia G. Nobile -- ============================================= Antonio Di Crescenzo Dipartimento di Matematica Università degli Studi di Salerno Via Giovanni Paolo II, n. 132 84084 Fisciano (SA) Italy Tel. +39-089-963349 Fax: +39-089-963303 E-mail: adicrescenzo(a)unisa.it Web: http://www.unisa.it/docenti/antoniodicrescenzo/index =============================================

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de Finetti Risk Seminar - October 2016
by Emanuela Rosazza 23 Oct '16

23 Oct '16

On behalf of the Scientific Committee of the de Finetti Risk Seminars, we are glad to invite you to participate at the following Lecture Warner Marzocchi Istituto nazionale di Geofisica e vulcanologia TITLE: The probabilistic nature of earthquake forecasting: key issues, challenges and testability LOCATION: The seminar will be held on Wednesday, October 26, at 18.00 at room 3-E4-SR03, Bocconi University, Via Rontgen 1, 3rd floor, Milano. A refreshment will be offered at 17.30. Scientific Committee: Prof. Simone Cerreia-Voglio (Univ. Bocconi) Prof. Marco Frittelli (Univ. degli Studi di Milano) Prof. Fabio Maccheroni (Univ. Bocconi) Prof. Massimo Marinacci (Univ. Bocconi) Prof. Emanuela Rosazza Gianin (Univ. Milano-Bicocca) Dott. Marco Maggis (Univ. degli Studi di Milano) **************************************************** 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 *****************************************************

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Annual ESOBE 2016 meeting, 27/28 October, Ca' Foscari University, Venice, Italy
by Roberto Casarin VE 22 Oct '16

22 Oct '16

7th ANNUAL EUROPEAN SEMINAR ON BAYESIAN ECONOMETRICS ESOBE 2016 Venice, Italy 27 - 28 October 2016 The workshop is organised by the Department of Economics of the *University Ca’ Foscari of Venice*, and is co-sponsored by the *European Central Bank*, the *Central Bank of Italy*, the *International Association for Applied Econometrics* and *GRETA Associati*. The ESOBE meetings aim at bringing together researchers and professionals interested in the application of Bayesian inference. Ever since the pioneering work of Arnold Zellner, Bayesian econometrics has expanded enormously in areas such as economics, finance, business, and marketing. The computational revolution in simulation techniques is a key ingredient in this expansion and allows the application of Bayesian methods to increasingly complex models and high-dimensional data environments. The ESOBE 2016 conference intends to discuss about research and application in the following *areas*: - Bayesian financial econometrics - Bayesian microeconometrics and program evaluation - Bayesian nonparametric - Shrinkage estimation and variable selection in high dimensions - Computational methods for large datasets - Efficient MCMC and SMC methods for complex models The *keynote speakers *of ESOBE 2016 are: - Christian P. Robert (University Paris Dauphine and University of Warwick) - Ulrich K. Mueller (Princeton University) - Thomas J. Sargent (New York University) The *Scientific Committee* consists of: - Monica Billio (Ca’ Foscari University of Venice) - Fabio Canova (BI Norwegian Business School) - Roberto Casarin (Ca’ Foscari University of Venice) - Sylvia Fruehwirth-Schnatter (Wirtschaftsuniversität Wien) - Sylvia Kaufmann (Study Center Gerzensee) - Gary Koop (Strathclyde Business School) - Francesco Ravazzolo (Free University of Bozen/Bolzano) - Herman K. van Dijk (Erasmus University Rotterdam and VU University Amsterdam) More detailed information available on the Conference *website*: http://virgo.unive.it/esobe2016/index.htm (* Apologies for post-crossing) -- Roberto Casarin University Ca' Foscari, Venice Address: San Giobbe 873/b 30121 Venezia, Italy Phone: +39 041.234.91.49 Fax: +39 041.234.91.76 Web:http://venus.unive.it/r.casarin/

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