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BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211124T160000
DTEND;TZID=Europe/Rome:20211124T170000
DTSTAMP:20260526T053423
CREATED:20211117T161316Z
LAST-MODIFIED:20211117T161339Z
UID:3705-1637769600-1637773200@datascience.unifi.it
SUMMARY:DISIA Seminar: Innovation on methods for the evaluation of the short-term health effects of environmental hazards
DESCRIPTION:Title: Innovation on methods for the evaluation of the short-term health effects of environmental hazards. \nSpeaker: Francesco Sera (DiSIA) e Dominic Royé (University of Santiago de Compostela) \nLocation: Aula 205 (ex 32) – DISIA – Viale Morgagni 59 The participation on site is restricted to max 20 people (need to register here https://labdisia.disia.unifi.it/reserve205/). However\, the seminar will be also online and you can participate at the following link: http://meet.google.com/aio-dhut-nah \nYou can find the abstract here: Abstract
URL:https://datascience.unifi.it/index.php/event/disia-seminar-innovation-on-methods-for-the-evaluation-of-the-short-term-health-effects-of-environmental-hazards/
LOCATION:DiSIA\, viale Morgagni 59\, Viale Morgagni 59\, Firenze\, Italy
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211123T113000
DTEND;TZID=Europe/Rome:20211123T123000
DTSTAMP:20260526T053423
CREATED:20211118T102942Z
LAST-MODIFIED:20211118T103059Z
UID:3710-1637667000-1637670600@datascience.unifi.it
SUMMARY:Seminar for "Nobel Prize for Economics 2021"
DESCRIPTION:The Florence Center for Data Science is happy to invite you to the Seminar for “Nobel Prize for Economics 2021” organized by the DISEi and the School of Economics and Management of the University of Florence that will take place Tuesday 23rd of November 2021. \nClick here to book your seat in advance. Soon we will provide the link for the live streaming. \nThis event will be in Italian.
URL:https://datascience.unifi.it/index.php/event/seminar-for-nobel-prize-for-economics-2021/
LOCATION:D6 Via delle Pandette 9\, Via delle Pandette 9\, Firenze\, Italy
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://datascience.unifi.it/wp-content/uploads/2021/11/Locandina-e1638374795116.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211112T140000
DTEND;TZID=Europe/Rome:20211112T153000
DTSTAMP:20260526T053423
CREATED:20211011T090504Z
LAST-MODIFIED:20211117T161020Z
UID:3604-1636725600-1636731000@datascience.unifi.it
SUMMARY:7th Seminar of the “D2 Seminar Series” – Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the seventh Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 12th of November 2021\, from 2-3.30 pm. \nThe seminar will be held by Luigi Brugnano from the Department of Mathematics and Computer Science “Ulisse Dini” and Veronica Ballerini from the Department of Statistics\, Computer Science and Applications “G. Parenti” of the University of Florence. \nRegister in advance for this webinar:https://us02web.zoom.us/webinar/register/WN_hjjYNaS1Tmqz1debdP-BQA \nAfter registering\, you will receive a confirmation email containing information about joining the webinar. \n \n———————————————\n\nSpeaker: Luigi Brugnano – Department of Mathematics and Computer Science “Ulisse Dini”\, University of Florence \nTitle: Recent advances in bibliometric indexes and their implementation \nAbstract: Bibliometric indexes are nowadays very commonly used for assessing scientific production\, research groups\, journals\, etc. It must be stressed that such indexes cannot substitute to enter the merit of the specific research but\, nonetheless\, they can provide a gross evaluation of its impact on the scientific community. That premise\, the currently used indexes often have drawbacks and/or sensibly vary for different subjects of investigation. For this reason\, in [1] an alternative index has been proposed\, based on an idea akin to that of the Google PageRank. Its actual implementation has been recently done in the Scopus database [2]. In this talk\, the basic facts and results of this approach will be recalled. \n[1] P.Amodio\, L.Brugnano. Recent advances in bibliometric indexes and the PaperRank problem. Journal of Computational and Applied Mathematics 267 (2014) 182-194. http://doi.org/10.1016/j.cam.2014.02.018 \n[2] P.Amodio\, L.Brugnano\, F.Scarselli. Implementation of the PaperRank and AuthorRank indices in the Scopus database. Journal of Infometrics 15 (2021) 101206. https://doi.org/10.1016/j.joi.2021.101206 \n  \nSpeaker: Veronica Ballerini – Department of Statistics\, Computer Science\, Applications “G. Parenti”\, University of Florence \nTitle: Fisher’s Noncentral Hypergeometric Distribution for the Size Estimation of Unemployed Graduates in Italy (joint work with Brunero Liseo\, University Sapienza di Roma) \nAbstract: To quantify unemployment among those who have never been employed is often tough. The lack of an administrative data flow attributable to such individuals makes them an elusive population. Hence\, one must rely on surveys. However\, individuals’ response rates to questions on their occupation may differ according to their employment status\, implying a not-at-random missing data generation mechanism. We exploit the underused Fisher’s noncentral hypergeometric distribution (FNCH) to solve such a biased urn experiment. FNCH has been underemployed in the statistical literature mainly because of the computational burden given by its probability mass function. Indeed\, as the number of draws and the number of different categories in the population increases\, any method involving the evaluation of the likelihood is practically unfeasible. Firstly\, we present a methodology that allows the approximation of the posterior distribution of the population size via MCMC and ABC methods. Then\, we apply such methodology to the case of graduated unemployed in Italy\, exploiting information from different data sources.
URL:https://datascience.unifi.it/index.php/event/7th-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Onine
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://datascience.unifi.it/wp-content/uploads/2021/05/Sfondo-D2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211105T143000
DTEND;TZID=Europe/Rome:20211105T153000
DTSTAMP:20260526T053423
CREATED:20211102T114638Z
LAST-MODIFIED:20211102T140229Z
UID:3669-1636122600-1636126200@datascience.unifi.it
SUMMARY:FDS Seminar: Giulia Iori from the City University of London
DESCRIPTION:Due to technical problems during the 6th seminar\, we were not able to listen to the seminar of Giulia Iori. That’s why the Florence Center for Data Science is happy to invite you again to the seminar on “Performance-based research funding: Evidence from the largest natural experiment worldwide” which is going to be held online Friday 5th of November 2021\, from 2.30-3.30 pm. \nThe seminar will be held by Giulia Iori from the Department of Economics of the City University of London. \nRegister for this webinar: https://us02web.zoom.us/webinar/register/WN_M2w6xh0yT9OMKGcqNztFpw \n  \nSpeaker: Giulia Iori – Department of Economics of the City University of London \nTitle: Performance-based research funding: Evidence from the largest natural experiment worldwide \nAbstract: The Research Excellence Framework (REF) is the main UK government policy on public research in the last 30 years. The primary aim of this policy is to promote and reward research excellence through competition for scarce research resources. Surprisingly\, and despite the severe criticisms\, little has been done to systematically evaluate its effects. In this paper\, we evaluate the impact of the REF 2014. We exploit a large database that contains all publications in Economics\, Business\, Management\, and Finance available in Scopus since 2001. We use a synthetic control method to compare the performance of each of the universities from the UK with counter-factual similar units in terms of past research constructed using data for US universities. We find a significant positive increase\, relative to the control group\, in the number of published papers\, and in the proportion of papers published in highly ranked journals within the Economics/Econometrics area and the Business\, Management and Finance area. Both Russell and non-Russell Group universities benefited from the REF\, with the Russell Group universities experiencing an overall significant increase in the number of publications and number of publications in top journals\, and the non-Russell group experiencing a significant increase in the proportion of publications in top journals in all areas. Interestingly\, the non-Russell group experienced a comparatively stronger increase in the proportion of top publications in Economics/Econometrics while the Russell Group experienced a comparatively stronger increase in the proportion of top publications in Business\, Management and Finance. However\, we see an insignificant effect when we focus on per-author output measures indicating that growth in output was mostly achieved by an increase in the number of research active academics rather than an overall increase in research productivity.
URL:https://datascience.unifi.it/index.php/event/fds-seminar-giulia-iori-from-the-city-university-of-london/
LOCATION:Onine
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211029T140000
DTEND;TZID=Europe/Rome:20211029T153000
DTSTAMP:20260526T053423
CREATED:20211011T090404Z
LAST-MODIFIED:20211117T161037Z
UID:3600-1635516000-1635521400@datascience.unifi.it
SUMMARY:6th Seminar of the “D2 Seminar Series” – Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the sixth Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 29th of October 2021\, from 2.30-4 pm. \nThe seminar will be held by Giulia Iori from the Department of Economics\, School of Social Science of the City University of London and Massimo Fornasier from the Department of Mathematics of the Technical University of Munich. \nRegister in advance for this webinar:https://us02web.zoom.us/webinar/register/WN_B20LTH2CR1SrVYCcD0Eqlw \nAfter registering\, you will receive a confirmation email containing information about joining the webinar. \n——————————————— \nSpeaker: Giulia Iori – Department of Economics\, School of Social Science of the City University of London \nTitle: Performance-based research funding: Evidence from the largest natural experiment worldwide \nAbstract: The Research Excellence Framework (REF) is the main UK government policy on public research in the last 30 years. The primary aim of this policy is to promote and reward research excellence through competition for scarce research resources. Surprisingly\, and despite the severe criticisms\, little has been done to systematically evaluate its effects. In this paper\, we evaluate the impact of the REF 2014. We exploit a large database that contains all publications in Economics\, Business\, Management\, and Finance available in Scopus since 2001. We use a synthetic control method to compare the performance of each of the universities from the UK with counter-factual similar units in terms of past research constructed using data for US universities. We find a significant positive increase\, relative to the control group\, in the number of published papers\, and in the proportion of papers published in highly ranked journals within the Economics/Econometrics area and the Business\, Management and Finance area. Both Russell and non-Russell Group universities benefited from the REF\, with the Russell Group universities experiencing an overall significant increase in the number of publications and number of publications in top journals\, and the non-Russell group experiencing a significant increase in the proportion of publications in top journals in all areas. Interestingly\, the non-Russell group experienced a comparatively stronger increase in the proportion of top publications in Economics/Econometrics while the Russell Group experienced a comparatively stronger increase in the proportion of top publications in Business\, Management and Finance. However\, we see an insignificant effect when we focus on per-author output measures indicating that growth in output was mostly achieved by an increase in the number of research active academics rather than an overall increase in research productivity. \nSpeaker: Massimo Fornasier – Department of Mathematics of the Technical University of Munich \nTitle: Consensus-based optimization \nAbstract: Consensus-based optimization (CBO) is a multi-agent metaheuristic derivative-free optimization method that can globally minimize nonconvex nonsmooth functions and is amenable to theoretical analysis. In fact\, optimizing agents (particles) move on the optimization domain driven by a drift towards an instantaneous consensus point\, which is computed as a convex combination of particle locations\, weighted by the cost function according to Laplace’s principle\, and it represents an approximation to a global minimizer. The dynamics are further perturbed by a random vector field to favor exploration\, whose variance is a function of thedistance of the particles to the consensus point. Based on an experimentally supported intuition that CBO always performs a gradient descent of the squared Euclidean distance to the global minimizer\, we show a novel technique for proving the global convergence to the global minimizer in mean-field law for a rich class of objective functions. We further present formulations of CBO over compact hypersurfaces. We conclude the talk with a few numerical experiments\, which show that CBO scales well with the dimension and is extremely versatile. \nhttps://arxiv.org/pdf/2103.15130.pdf to appear in Found. Comput. Math.https://arxiv.org/pdf/2001.11994.pdf appeared in M3AShttps://arxiv.org/pdf/2001.11988.pdf appeared in J. Mach. Learn. Rechhttps://arxiv.org/pdf/2104.00420.pdf to appear in SIAM J. Opt.
URL:https://datascience.unifi.it/index.php/event/6th-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Online
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://datascience.unifi.it/wp-content/uploads/2021/05/Sfondo-D2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211028T120000
DTEND;TZID=Europe/Rome:20211028T133000
DTSTAMP:20260526T053423
CREATED:20211018T145412Z
LAST-MODIFIED:20211115T104224Z
UID:3651-1635422400-1635427800@datascience.unifi.it
SUMMARY:DISIA Seminar: Uncertainty across the “Contact Line”: armed conflict\, COVID-19\, and perceptions of fertility decline in Eastern Ukraine
DESCRIPTION:Title: Uncertainty across the “Contact Line”: armed conflict\, COVID-19\, and perceptions of fertility decline in Eastern Ukraine \nSpeaker: Brienna Perelli-Harris (University of Southampton) \nLocation: Aula 205 (ex 32) – DISIA – Viale Morgagni 59 The participation on site is restricted to max 15 people (need to contact raffaele.guetto@unifi.it). However\, the seminar will be also online and you can participate at the following link: meet.google.com/atb-qtxf-nvb You can find the abstract here: Abstract
URL:https://datascience.unifi.it/index.php/event/disia-seminar-uncertainty-across-the-contact-line-armed-conflict-covid-19-and-perceptions-of-fertility-decline-in-eastern-ukraine/
LOCATION:DiSIA\, viale Morgagni 59\, Viale Morgagni 59\, Firenze\, Italy
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211015T140000
DTEND;TZID=Europe/Rome:20211015T153000
DTSTAMP:20260526T053423
CREATED:20211008T085729Z
LAST-MODIFIED:20211117T161059Z
UID:3595-1634306400-1634311800@datascience.unifi.it
SUMMARY:5th Seminar of the “D2 Seminar Series” – Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the fifth Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 15th of October 2021\, from 2-3.30 pm. \nThe seminar will be held by Leonardo Bargigli from the Department of Economics and Management of the University of Florence and Chiara Marzi from the Institute of Applied Physics ‘Nello Carrara’ (IFAC) – National Research Council (CNR). \nRegister in advance for this webinar:https://us02web.zoom.us/webinar/register/WN_3tq7BbbwTSeA956KFQIK0w \nAfter registering\, you will receive a confirmation email containing information about joining the webinar. \n——————————————— \nSpeaker: Leonardo Bargigli – Department of Economics and Management\, University of Florence \nTitle: Endogenous and Exogenous Volatility in the Foreign Exchange Market (with G. Cifarelli) \nAbstract: We study two sources of heteroscedasticity in high-frequency financial data. The first\, endogenous\, source is the behaviour of bounded rational market participants. The second\, exogenous\, source is the flow of market relevant information. We estimate the impact of the two sources jointly by means of a Markov switching (MS) SVAR model. Following the original intuition of Rigobon (2003)\, we achieve identification for all coefficients by assuming that the structural errors of the MS-SVAR model follow a GARCH-DCC process. Using transaction data of the EUR/USD interdealer market in 2016\, we firstly detect three regimes of endogenous volatility. Then we show that both kinds of volatility matter for the transmission of shocks\, and that the exogenous information is channelled to the market mostly through price variations. This suggests that\, on the FX market\, liquidity providers are better informed than liquidity takers\, who act mostly as feedback traders. The latter are able to profit from trade because\, unlike noise traders\, they respond immediately to the informative price shocks. \nSpeaker: Chiara Marzi – Institute of Applied Physics ‘Nello Carrara’ (IFAC) – National Research Council (CNR) \nTitle: Artificial Intelligence in Neuroimaging \nAbstract: Life sciences data coupled with Artificial Intelligence (AI) techniques can help researchers accurately pinpoint novel biomarkers. AI can propose new indices as potential biomarkers while simultaneously aiding in searching for hidden patterns among “well-established” indices. In this webinar\, we will take a brief journey through some applications of Machine Learning in neuroimaging. In the first part of the webinar\, we will talk about the not so easy “marriage” between AI and clinical data\, focusing on Big Data from Radiology Imaging and related issues. In the second part\, we will see how we can transfer mathematical\, physical\, and statistical ideas to the Neuroimaging domain and how AI can help this transfer. An example is the study of the structural complexity of the brain starting from MRI images\, using fractal analysis. The Fractal Dimension (FD) can be considered a measure of morphological changes due to healthy ageing and/or the onset of neurological diseases. The use of ML techniques can promote the candidature of FD as a biomarker for many neurological diseases.
URL:https://datascience.unifi.it/index.php/event/5th-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Onine
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://datascience.unifi.it/wp-content/uploads/2021/05/Sfondo-D2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211012T140000
DTEND;TZID=Europe/Rome:20211012T160000
DTSTAMP:20260526T053423
CREATED:20210927T102020Z
LAST-MODIFIED:20210927T102029Z
UID:3564-1634047200-1634054400@datascience.unifi.it
SUMMARY:DISEI Seminar: Istituzioni e Sviluppo Economico nel capitalismo contemporaneo
DESCRIPTION:Title: Istituzioni e Sviluppo Economico nel capitalismo contemporaneo \nSpeaker: Elisabetta Basile\, Luca Bortolotti\, Mario Biggeri\, Claudio Cecchi\, Franco Volpi The seminar will be held online. \nYou can find more information at the following link: https://www.disei.unifi.it/vp-360-seminari.html
URL:https://datascience.unifi.it/index.php/event/disei-seminar-istituzioni-e-sviluppo-economico-nel-capitalismo-contemporaneo/
LOCATION:Online
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211005T140000
DTEND;TZID=Europe/Rome:20211005T160000
DTSTAMP:20260526T053423
CREATED:20210927T101839Z
LAST-MODIFIED:20210927T101851Z
UID:3560-1633442400-1633449600@datascience.unifi.it
SUMMARY:DISEI Seminar: Global search for science: International knowledge flows between multinational companies and universities
DESCRIPTION:Title: Global search for science: International knowledge flows between multinational companies and universities \nSpeaker: Claudio Fassio (Lund University) \nThe seminar will be held online. You can find more information at the following link: https://www.disei.unifi.it/vp-360-seminari.html
URL:https://datascience.unifi.it/index.php/event/disei-seminar-global-search-for-science-international-knowledge-flows-between-multinational-companies-and-universities/
LOCATION:Onine
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20211004T170000
DTEND;TZID=Europe/Rome:20211004T180000
DTSTAMP:20260526T053423
CREATED:20210927T101422Z
LAST-MODIFIED:20210927T101506Z
UID:3555-1633366800-1633370400@datascience.unifi.it
SUMMARY:DISIA Seminar: Business Excellence 5.0
DESCRIPTION:Title: Business Excellence 5.0 \nSpeaker: Gabriele Arcidiacono (DIIE – Università Guglielmo Marconi\, Roma) \nThe Seminar will be held online on the Gmeet platform. To register send an email at the following email address: centro.steering@disia.unifi.it \nYou can find the abstract here: Abstract
URL:https://datascience.unifi.it/index.php/event/disia-seminar-business-excellence-5-0/
LOCATION:Onine
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210930T153000
DTEND;TZID=Europe/Rome:20210930T170000
DTSTAMP:20260526T053423
CREATED:20210927T101126Z
LAST-MODIFIED:20211018T145221Z
UID:3552-1633015800-1633021200@datascience.unifi.it
SUMMARY:DISIA Seminar: Ethnicity and Governing Party Support in Africa
DESCRIPTION:Title: Ethnicity and Governing Party Support in Africa \nSpeaker: Carlos G. Rivero (Valencia University & Centre for International and Comparative Politics\, Stellenbosch University) \nLocation: Aula 205 (ex 32) – DISIA – Viale Morgagni 59 \nThe participation on site is restricted to max 15 people (need to contact raffaele.guetto@unifi.it). However\, the seminar will be also online and you can participate at the following link: https://meet.google.com/hfw-mdvm-ity \nYou can find the abstract here:  Abstract
URL:https://datascience.unifi.it/index.php/event/disia-seminar-ethnicity-and-governing-party-support-in-africa/
LOCATION:DiSIA\, viale Morgagni 59\, Viale Morgagni 59\, Firenze\, Italy
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210702T143000
DTEND;TZID=Europe/Rome:20210702T153000
DTSTAMP:20260526T053423
CREATED:20210527T141652Z
LAST-MODIFIED:20210623T081853Z
UID:3291-1625236200-1625239800@datascience.unifi.it
SUMMARY:4th Seminar of the “D2 Seminar Series” – Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the fourth Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 2nd of July 2021\, from 2-3.30 pm. \nThe seminar will be held by Anna Gottard from the Department of  Statistics\, Computer Science\, Applications “G. Parenti” and Costanza Conti from the Department of Industrial Engineering of the University of Florence. \nRegister in advance for this webinar:\nhttps://us02web.zoom.us/webinar/register/WN_WkYeStnjRK6cincfDPXUZg \nAfter registering\, you will receive a confirmation email containing information about joining the webinar. \n——————————————— \nSpeaker: Anna Gottard – Department of Statistics\, Computer Science\, Applications “G. Parenti”\, University of Florence \nTitle: Circular data\, conditional independence & graphical models \nAbstract: Circular variables\, arising in several contexts and fields\, are characterized by periodicity. Models for studying the dependence/independence structure of circular variables are under-explored. We will discuss three multivariate circular distributions\, the von Mises\, the Wrapped Normal and the Inverse Stereographic distributions\, focusing on their properties concerning conditional independence. For each of these distributions\, we examine the main properties related to conditional independence and introduce suitable classes of graphical models. The usefulness of the proposal is shown by modelling the conditional independence among dihedral angles characterizing the three-dimensional structure of some proteins. \nSpeaker: Costanza Conti – Department of Industrial Engineering\, University of Florence \nTitle: Penalized hyperbolic-polynomial splines\n(Joint work with: Rosanna Campagna\, Universit`a degli Studi della Campania “L. Vanvitelli”) \nAbstract: The advent of P-splines\, first introduced by Eilers and Marx in 2010 (see [4])\, has led to important developments in data regression through splines. With the aim of generalizing polynomial P-splines\, in [1] we have recently defined a model of penalized regression spline\, called HP-spline\, in which polynomial B-spline functions are replaced by Hyperbolic-Polynomial bell-shaped basis functions. HP-splines are defined as a solution to a minimum problem characterized by a discrete penalty term. They inherit from P-splines the advantages of the model\, like the separation of the data from the spline nodes\, so avoiding the problems of overfitting and the consequent oscillations at the edges. HP-splines are particularly interesting in different applications that require analysis and forecasting of data with exponential trends. Indeed\, the starting idea is the definition of a polynomial-exponential smoothing spline model to be used in the framework of the Laplace transform inversion as done in [2\,3]. We present some recent results on the existence\, uniqueness\, and reproduction properties of HP-splines\, also with the aim of extending their usage to data analysis. \n[1] C. Conti\, R. Campagna\, Penalized exponential-polynomial splines\, Appl. Math. Letters\, 118\, (2021) 107–159 \n[2] R. Campagna\, C. Conti\, S. Cuomo\, Computational Error Bounds for Laplace Transform Inversion Based on Smoothing Splines\, Appl. Math. Comput.\, 383\, (2020) 125–376 \n[3] R. Campagna\, C. Conti\, S. Cuomo\, Smoothing exponential-polynomial splines for multiexponential decay data\, Dolomites Research note on Approximation (2019) 86–10 \n[4] P.H.C. Eilers and B.D.Marx\, Splines\, knots\, and penalties\, WIREs Comp. Stat.\, 2\, (2010) 637-653.
URL:https://datascience.unifi.it/index.php/event/4th-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Onine
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210629T160000
DTEND;TZID=Europe/Rome:20210629T170000
DTSTAMP:20260526T053423
CREATED:20210628T132200Z
LAST-MODIFIED:20210628T132617Z
UID:3479-1624982400-1624986000@datascience.unifi.it
SUMMARY:DISEI Seminar: Assessing and designing research\, projects and policies in energy\, climate and AI
DESCRIPTION:DETAILS \nTitle: Assessing and designing research\, projects and policies in energy\, climate and AI \nSpeaker: Francesco Fuso-Nerini (KTH) \nhttps://www.disei.unifi.it/vp-360-seminari.html \nMeeting Link: https://unifirenze.webex.com/unifirenze/j.php?MTID=m3908103502626beac5efee7bf699f135\nMeeting Number: 121 695 9503\nPassword: NkFUXXWP566
URL:https://datascience.unifi.it/index.php/event/disei-seminar-assessing-and-designing-research-projects-and-policies-in-energy-climate-and-ai/
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210629T140000
DTEND;TZID=Europe/Rome:20210629T150000
DTSTAMP:20260526T053423
CREATED:20210618T134216Z
LAST-MODIFIED:20210629T082930Z
UID:3447-1624975200-1624978800@datascience.unifi.it
SUMMARY:DISEI Seminar: A soft introduction to applied Machine Learning for Social Sciences
DESCRIPTION:THE SEMINAR HAS BEEN CANCELLED \n  \nDETAILS \nTitle: A soft introduction to applied Machine Learning for Social Sciences \nSpeaker: Rafael Boix\, Universidad de Valencia \nhttps://www.disei.unifi.it/vp-360-seminari.html \nMeeting Link: https://unifirenze.webex.com/unifirenze/j.php?MTID=m3908103502626beac5efee7bf699f135\nMeeting Number: 121 695 9503\nPassword: NkFUXXWP566
URL:https://datascience.unifi.it/index.php/event/disei-seminar-a-soft-introduction-to-applied-machine-learning-for-social-sciences/
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210618T140000
DTEND;TZID=Europe/Rome:20210618T153000
DTSTAMP:20260526T053423
CREATED:20210527T141606Z
LAST-MODIFIED:20211008T082232Z
UID:3287-1624024800-1624030200@datascience.unifi.it
SUMMARY:3rd Seminar of the “D2 Seminar Series” – Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the third Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 18th of June 2021\, from 2-3.30 pm.\n\nThe Seminar will be held by two new Fellows of the Center: the research unit COPERNICUS Earth Observation and Spatial Analysis and some researchers of the Magnetic Resonance Center (CERM). The speakers are Gherardo Chirici from the Department of Agriculture\, Food\, Environment and Forestry (University of Florence) and Enrico Ravera from the Magnetic Resonance Center (CERM) and the Department of Chemistry (University of Florence).\n\nRegister in advance for the seminar (free of charge): https://us02web.zoom.us/webinar/register/WN_I9bCjz_cQ_K_8nOP94usTw\n\nAfter registering\, you will receive a confirmation email containing information about joining the webinar.\n\n—————-\n\nSpeaker: Enrico Ravera – Magnetic Resonance Center (CERM) and Department of Chemistry\, University of Florence\n\nTitle: From algebra to biology: what does the math of ensemble averaging methods can tell us\n\nAbstract: Our work aims at a quantitative comparison of different methods for reconstructing conformational ensembles of biological macromolecules integrating molecular simulations and experimental data. This field has evolved over the years reflecting the evolution of computational power and sampling schemes\, and a plethora of different methods have been proposed. These methods can vary extensively in terms of how the prior information from the simulation is used to reproduce the experimental data\, but can be coarsely attributed to two categories: Maximum Entropy or Maximum Parsimony. In any case\, the problem is severely underdetermined and therefore additional information needs to be provided on the basis of the chemical knowledge about the system under investigation. Maximum entropy looks for the minimal perturbation of the prior distribution\, whereas Maximum Parsimony looks for the smallest possible ensemble that can explain in full the experimental data. On these grounds\, one can expect radically different solutions in the reconstruction\, but surprises are still possible – and can be justified by a rigorous geometrical description of the different methods.\n\nSpeaker: Gherardo Chirici – COPERNICUS Earth Observation and Spatial Analysis and Department of Agriculture\, Food\, Environment and Forestry\, University of Florence\n\nTitle: Big data from space. Recent Advances in Remote Sensing Technologies\n\nAbstract: Since the 1970s\, remote sensing technologies for terrestrial observation have generated a constant flow of data from different platforms\, in different formats and with different purposes. From these\, through successive steps\, spatial information is generated to support the Earth resources monitoring and planning. Indispensable in various sectors: from urban planning to geology\, from agriculture to forest monitoring and\, more generally\, any type of information to support environmental monitoring. For this reason\, remotely sensed information is recognized as a typical example of big data ante litteram. Today the new cloud computing technologies (such as Google Earth Engine) allow facing the complex problem of data management and processing of big data from remote sensing with new strategies that have revolutionized these data sources are used. From experiments on small areas\, today we have moved to the possibility of operationally processing vast multidimensional and multitemporal datasets on a global scale. The increased availability of information from space is exemplified by the numerous services offered by the European Copernicus program. The presentation\, starting from a brief introduction to remote sensing techniques\, illustrates some examples of applications developed within the geoLAB – Geomatics Laboratory of the Department of Agriculture\, Food\, Environment and Forestry (DAGRI) and the UNIFI COPERNICUS Research Unit.\n\n 
URL:https://datascience.unifi.it/index.php/event/3rd-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Online
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210604T140000
DTEND;TZID=Europe/Rome:20210604T153000
DTSTAMP:20260526T053423
CREATED:20210525T105728Z
LAST-MODIFIED:20210527T103647Z
UID:3340-1622815200-1622820600@datascience.unifi.it
SUMMARY:2nd Seminar of the “D2 Seminar Series” – Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the second Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 4th of June 2021\, from 2-3.30 pm. \nThe seminar will be held by Assistant Professor Cesare Bracco\, PhD from the Department of Mathematics and Computer Science “Ulisse Dini” and Professor Leonardo Boncinelli from the Department of Economics and Management of the University of Florence. \nRegister her for the event (free of charge): Registration 2nd Seminar  \n  \nSpeaker: PhD Cesare Bracco \nDepartment of Mathematics and Computer Science “Ulisse Dini”\, University of Florence\nTitle: Scattered data: surface reconstruction and fault detection (joint work with O. Davydov\, C. Giannelli\, D. Großmann\, S. Imperatore\, D. Mokriš\, A. Sestini) \nAbstract: We will consider two aspects concerning scattered data approximation. The first is reconstructing a (parametrized) surface from a set of scattered points: the lack of structure in the data requires approximation methods that automatically adapt to the distribution and shape of the data themselves. We will discuss an effective approach to this issue based on hierarchical spline spaces\, which can be locally refined\, and therefore naturally lead to adaptive algorithms. The reconstruction problem contains another interesting problem: detecting the discontinuities the surface may have in order to reproduce them. Finding the discontinuity curves\, usually called faults (or gradient faults when gradient discontinuities are considered)\, is actually an important issue in itself\, with several applications\, for example in image processing and geophysics. I will present a method to determine which points in the scattered data set lie close to a (gradient) fault\, based on indicators obtained by using numerical differentiation formulas. \nSpeaker: Professor Leonardo Boncinelli \nDepartment of Economics and Management\, University of Florence\nTitle: Game-based education promotes sustainable water use \nAbstract: In this study\, we estimate the impact of a game-based educational program aimed at promoting sustainable water usage among 2nd-4th grade students and their families living in the municipality of Lucca\, Italy. To this purpose\, we exploited unique data from a quasi-experiment involving about two thousand students\, one thousand participating (the treatment group)\, and one thousand not participating (the control group) in the program. Data were collected by means of a survey that we specifically designed and implemented for collecting students’ self-reported behaviours. Our estimates indicate that the program has been successful: the students in the program reported an increase in efficient water usage and an increase in the frequency of discussions with their parents about water usage; moreover\, positive effects were still observed after six months. Our findings suggest that game-based educational programs can be an effective instrument to promote sustainable water consumption behaviors in children and their parents.
URL:https://datascience.unifi.it/index.php/event/2nd-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Online
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210521T140000
DTEND;TZID=Europe/Rome:20210521T153000
DTSTAMP:20260526T053423
CREATED:20210512T093422Z
LAST-MODIFIED:20210514T135957Z
UID:3276-1621605600-1621611000@datascience.unifi.it
SUMMARY:1st Seminar of the "D2 Seminar Series" - Florence Center for Data Science
DESCRIPTION:The Florence Center for Data Science is happy to present the first Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will be held online Friday 21st of May 2021\, from 2-3.30 pm. \nHere the link for the Registration:  https://forms.gle/1AvggjTGfKs1Xxy3A \nSpeaker: Professor Fabrizia Mealli\nDepartment of Statistics\, Computer Science\, Applications “G. Parenti”\, University of Florence\nTitle: Assessing causality under interference \nAbstract: Causal inference from non-experimental data is challenging; it is even more challenging when units are connected through a network. Interference issues may arise\, in that potential outcomes of a unit depend on its treatment as well as on the treatments of other units\, such as their neighbours in the network. In addition\, the typical unconfoundedness assumption must be extended—say\, to include the treatment of neighbours\, and individual and neighbourhood covariates—to guarantee identification and valid inference. These issues will be discussed\, new estimands introduced to define treatment and interference effects and the bias of a naive estimator that wrongly assumes away interference will be shown. A covariate-adjustment method leading to valid estimates of treatment and interference effects in observational studies on networks will be introduced and applied to a problem of assessing the effect of air quality regulations (installation of scrubbers on power plants) on health in the USA. \nSpeaker: Professor Andrew Bagdanov\nDepartment of Information Engineering\, University of Florence\nTitle: Lifelong Learning at the end of the (new) Early Years \nAbstract: Lifelong learning\, also often referred to as continual or incremental learning\, refers to the training of artificially intelligent systems able to continuously learn to address new tasks from new data while preserving knowledge learned from previously learned ones. Lifelong learning is currently enjoying a sort of renaissance due to renewed interest from the Deep Learning community. In this seminar\, I will introduce the overall framework of continual learning\, discuss the fundamental role played by the stability-plasticity dilemma in understanding catastrophic forgetting in lifelong learning systems\, and present a broad panorama of recent results in class-incremental learning. I will conclude the discussion with a look at current trends\, open problems\, and low-hanging opportunities in this area.
URL:https://datascience.unifi.it/index.php/event/1st-seminar-of-the-d2-seminar-series-florence-center-for-data-science/
LOCATION:Online
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20210215T170000
DTEND;TZID=Europe/Rome:20210215T183000
DTSTAMP:20260526T053423
CREATED:20210212T110842Z
LAST-MODIFIED:20210212T110842Z
UID:3234-1613408400-1613413800@datascience.unifi.it
SUMMARY:Kick-off Meeting - Master II Livello DATA SCIENCE AND STATISTICAL LEARNING - MD2SL
DESCRIPTION:We are pleased to announce the kick-off meeting for the MD2SL Master\, which will be held on February 15th at 17:00.\nFurther details are available at this link.
URL:https://datascience.unifi.it/index.php/event/kick-off-meeting-master-ii-livello-data-science-and-statistical-learning-md2sl/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200928T150000
DTEND;TZID=Europe/Rome:20200928T170000
DTSTAMP:20260526T053423
CREATED:20200903T110017Z
LAST-MODIFIED:20200903T125103Z
UID:2852-1601305200-1601312400@datascience.unifi.it
SUMMARY:CEN-IBS/GMDS Invited Session on "Causal Inference and Machine Learning"
DESCRIPTION:“Causal Inference and Machine Learning” – a virtual\nsatellite invited session of the 2020 joint conference of the GMDS &\nCEN-IBS – 28 September\, 3-5pm (CEST\, Berlin time). \nMore information on the website https://www.eventbrite.de/e/cen-ibsgmds-invited-session-on-causal-inference-and-machine-learning-tickets-116222778459 \nNote: the event is free\, but you need to register via this eventbrite site https://www.eventbrite.de/e/cen-ibsgmds-invited-session-on-causal-inference-and-machine-learning-tickets-116222778459
URL:https://datascience.unifi.it/index.php/event/cen-ibs-gmds-invited-session-on-causal-inference-and-machine-learning/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200608T080000
DTEND;TZID=Europe/Rome:20200612T170000
DTSTAMP:20260526T053423
CREATED:20191206T150618Z
LAST-MODIFIED:20191229T170154Z
UID:2430-1591603200-1591981200@datascience.unifi.it
SUMMARY:2020 Applied Bayesian Statistics Summer School: BAYESIAN CAUSAL INFERENCE
DESCRIPTION:The Applied Bayesian Statistics summer school has been running since 2004. Since 2012 it is organised by: \n\nIMATI CNR Istituto di Matematica Applicata e Tecnologie Informatiche\, Consiglio Nazionale delle Ricerche\, Milano\nDipartimento di Scienze Statistiche Università Cattolica\, Milano\n\nThe 2020 Applied Bayesian Statistics Summer School (17th edition) will be held in Florence\, Italy. The topic chosen for the 2020 school is\nBayesian Causal Inference. The lecturer is Prof. Fan Li (Department of Statistical Science\, Duke University\, Durham\, NC\, USA).\nFurther details are provided on the conference webpage. \nLocal contributing organization:\nFlorence Center for Data Science (FDS)\nDepartment of Statistics\, Computer Science\, Applications (DISIA)\, University of Florence
URL:https://datascience.unifi.it/index.php/event/2020-applied-bayesian-statistics-summer-school-bayesian-causal-inference/
LOCATION:DiSIA\, viale Morgagni 59\, Viale Morgagni 59\, Firenze\, Italy
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200219T120000
DTEND;TZID=Europe/Rome:20200219T133000
DTSTAMP:20260526T053423
CREATED:20200207T143635Z
LAST-MODIFIED:20200207T143635Z
UID:2544-1582113600-1582119000@datascience.unifi.it
SUMMARY:DISIA Seminar: From logit to linear regression and back
DESCRIPTION:Title: From logit to linear regression and back \nSpeaker: Giovanni Maria Marchetti (University of Florence) \nLocation: Aula 32 – DISIA – Viale Morgagni 59 \nAbstract
URL:https://datascience.unifi.it/index.php/event/disia-seminar-from-logit-to-linear-regression-and-back/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200218T170000
DTEND;TZID=Europe/Rome:20200218T193000
DTSTAMP:20260526T053423
CREATED:20200129T094327Z
LAST-MODIFIED:20200129T094327Z
UID:2537-1582045200-1582054200@datascience.unifi.it
SUMMARY:DSG Seminar: The Future of Artificial Intelligence and Fundamental Rights
DESCRIPTION:Title: The Future of Artificial Intelligence and Fundamental Rights \nSpeaker: Marc Rotenberg (Georgetown Law School – EPIC) \nLocation: Building D4\, Room 102 \nSeminar poster
URL:https://datascience.unifi.it/index.php/event/dsg-seminar-the-future-of-artificial-intelligence-and-fundamental-rights/
LOCATION:D4 Via delle Pandette 9\, Via delle Pandette 9\, Firenze\, Italy
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200218T120000
DTEND;TZID=Europe/Rome:20200218T133000
DTSTAMP:20260526T053423
CREATED:20200207T143056Z
LAST-MODIFIED:20200207T143056Z
UID:2542-1582027200-1582032600@datascience.unifi.it
SUMMARY:DISIA Seminar: On Spatial Lag Models estimated using crowdsourcing\, web-scraping or other unconventionally collected Big Data
DESCRIPTION:Title: On Spatial Lag Models estimated using crowdsourcing\, web-scraping or other unconventionally collected Big Data \nSpeaker: Giuseppe Arbia (Catholic University of the Sacred Heart Milan) \nLocation: Aula 32 – DISIA – Viale Morgagni 59 \nAbstract
URL:https://datascience.unifi.it/index.php/event/disia-seminar-on-spatial-lag-models-estimated-using-crowdsourcing-web-scraping-or-other-unconventionally-collected-big-data/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200129T113000
DTEND;TZID=Europe/Rome:20200129T123000
DTSTAMP:20260526T053423
CREATED:20200114T134059Z
LAST-MODIFIED:20200114T134143Z
UID:2528-1580297400-1580301000@datascience.unifi.it
SUMMARY:Adversarial Machine Learning
DESCRIPTION:Speaker: Prof. Fabio Roli\, Università di Cagliari \nMachine learning algorithms are widely used for cybersecurity\napplications\, including spam\, malware detection\, biometric recognition.\nIn these applications\, the learning algorithm has to face intelligent\nand adaptive attackers who can carefully manipulate data to purposely\nsubvert the learning process. As machine learning algorithms have not\nbeen originally designed under such premises\, they have been shown to be\nvulnerable to well-crafted attacks\, including test-time evasion and\ntraining-time poisoning attacks (also known as adversarial examples).\nThis talk aims to introduce the fundamentals of adversarial machine\nlearning and some techniques to assess the vulnerability of machine\nlearning algorithms to adversarial attacks. We report application\nexamples including object recognition in images\, biometric identity\nrecognition\, spam and malware detection. \n\n\n\n\n\nFabio Roli is a Full Professor of Computer Engineering at the University\nof Cagliari\, Italy\, and Director of the Pattern Recognition and\nApplications laboratory (http://pralab.diee.unica.it/). He is partner\nand R&D manager of the company Pluribus One that he co-founded\n(https://www.pluribus-one.it ). He has been doing research on the design\nof pattern recognition and machine learning systems for thirty years.\nHis current h-index is 66 according to Google Scholar (December 2019).\nHe has been appointed Fellow of the IEEE and Fellow of the International\nAssociation for Pattern Recognition. He was a member of NATO advisory\npanel for Information and Communications Security\, NATO Science for\nPeace and Security (2008 – 2011).
URL:https://datascience.unifi.it/index.php/event/adversarial-machine-learning/
LOCATION:Aula Caminetto\, Via di Santa Marta 3\, Firenze\, Italy
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200120
DTEND;VALUE=DATE:20200123
DTSTAMP:20260526T053423
CREATED:20191230T120049Z
LAST-MODIFIED:20191230T120049Z
UID:2514-1579478400-1579737599@datascience.unifi.it
SUMMARY:DISIA hosts a 3-day Stats Camp Seminar
DESCRIPTION:The Department of Statistics is hosting a Todd D. Little (Texas Tech University) short course: \nTitle: The Craft of Model Construction Using Structural Equation Modeling\nComprehensive 3-day Stats Camp Seminar by Todd Little (Texas Tech University)\n\nSyllabus of the short course \nOnline registration  \n(For DiSIA members\, please contact Carla Rampichini) \n  \nBIO \nTodd D. Little\, Ph.D. is a Professor of Educational Psychology at Texas Tech University (TTU) where\, in 2013\, he became the founding director of the Institute for Measurement\, Methodology\, Analysis and Policy (IMMAP). The IMMAP at TTU is a University-designated research and support center that provides expert consulting and assistance on all manner of data collection\, data management\, and advanced statistical analyses. Little is internationally recognized for his quantitative work on various aspects of applied SEM (e.g.\, indicator selection\, parceling\, modeling developmental processes) as well as his substantive developmental research (e.g.\, action-control processes and motivation\, coping\, and self-regulation). Prior to joining TTU\, Little has guided quantitative training and provided consultation to students\, staff\, and faculty at the Max Planck Institute for Human Development’s Center for Lifespan Studies (1991-1998)\, Yale University’s Department of Psychology (1998-2002)\, and researchers at KU (2002-2013\, including as director of the RDA unit at the Lifespan Institute and as director of the Center for Research Methods and Data Analysis). In 2001\, Little was elected to membership in the Society for Multivariate Experimental Psychology\, a restricted-membership society of quantitative specialists in the behavioral and social sciences. \nIn 2009\, he was elected President of APA’s Division 5 (Evaluation\, Measurement\, and Statistics). He founded\, organizes\, and teaches in the internationally renowned ‘Stats Camps’ each June (see statscamp.org for details of the summer training programs) and has given over 150 workshops and talks on methodology topics around the world. As an interdisciplinary-oriented collaborator\, Little has published with over 280 persons from around the world in over 65 different peer-reviewed journals. His work has garnered over 11\,000 citations. He published Longitudinal Structural Equation Modeling in 2013 and he has edited five books related to methodology\, including the Oxford Handbook of Quantitative Methods and the Guildford Handbook of Developmental Research Methods (with Brett Laursen and Noel Card). Little has served on numerous grant review panels for federal agencies such as NSF\, NIH\, and IES\, and private foundations such as the Jacobs Foundation. He has been the principal investigator or co-principal investigator on over 15 grants and contracts and he has served as a statistical consultant on over 70 grants and contracts. In the conduct of his collaborative research\, he has participated in the development of over 12 different measurement tools\, including the CAMI\, the Multi-CAM\, the BALES\, the BISC\, the I FEEL\, and the form/function decomposition of aggression.
URL:https://datascience.unifi.it/index.php/event/disia-hosts-a-3-day-stats-camp-seminar/
LOCATION:DiSIA\, viale Morgagni 59\, Viale Morgagni 59\, Firenze\, Italy
CATEGORIES:Short course
ATTACH;FMTTYPE=image/png:https://datascience.unifi.it/wp-content/uploads/2019/12/little.jpg.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200116T150000
DTEND;TZID=Europe/Rome:20200116T160000
DTSTAMP:20260526T053423
CREATED:20200112T213154Z
LAST-MODIFIED:20200112T213154Z
UID:2523-1579186800-1579190400@datascience.unifi.it
SUMMARY:Self-Organizing Migrating Algorithm - Progress\, Innovations and Applications
DESCRIPTION:Speaker: Prof. Ivan Zelinka\nLocation: Sala riunioni DINFO – Via di S. Marta 3\nThis seminar discusses recent advances\, progress and application on SOMA algorithm (http://somaalgorithm.com)\, that has been developed in the year 2000 and is based on swarm intelligence principles. During its existence it has been published twice in a book form\, numerous journals and was a subject of a few keynotes and tutorials. Recent improvements of this algorithms\, published on Congress on Evolutionary Algorithms\, GECCO and SEMCCO have set up its performance on the same level as the differential evolution is (actually on the 3rd place amongst the 34 state-of-art algorithms of global optimization like PSO\, DE\, ABC\, FireFly\,…). In the seminar will be audience introduced to its latest improvements and modification\, testing on representative test functions as well as applications of the SOMA. Selected applications will be from domain of chaos control\, real-time control of the plasma reactor\, symbolic regression – program synthesis\, swarm robot control\, design of electronic circuits\, neural network synthesis\, computer games and astrophysical data processing amongst the others. The seminar is designed as an introduction into SOMA\, its structure\, results\, and content are based on our previous research\, journal publications\, keynotes\, and tutorials and reflect the latest progress in that field.
URL:https://datascience.unifi.it/index.php/event/self-organizing-migrating-algorithm-progress-innovations-and-applications/
LOCATION:Sala riunioni DINFO\, Via di Santa Marta 3\, Firenze\, Italy
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20200114T150000
DTEND;TZID=Europe/Rome:20200114T160000
DTSTAMP:20260526T053423
CREATED:20200112T212553Z
LAST-MODIFIED:20200112T213238Z
UID:2519-1579014000-1579017600@datascience.unifi.it
SUMMARY:Recent Advances and Progress in Evolutionary Algorithms and its Dynamics
DESCRIPTION:Title: Recent Advances and Progress in Evolutionary Algorithms and its Dynamics \nSpeaker: Prof. Ivan Zelinka \nLocation: Sala riunioni DINFO \n\n\n\n\n\n\n\n\n\n\n\n\n\nThis seminar is focused on recent progress in the mutual intersection of a few exciting fields of research whose core topic is evolutionary algorithms in general and will be explained relations between evolutionary dynamics\, its visualization as a complex network and its control. It discusses research in evolutionary algorithms that can be considered a discrete dynamical complex system with inherent nonlinear dynamics. These dynamics is visualized and analyzed as a complex network and CML (coupled map lattices) systems. As already reported in many research papers and books\, these dynamics can generate different kinds of behavior including chaotic one. Selected evolutionary algorithms discussed in this seminar will be differential evolution\, genetic algorithm\, particle swarm\, artificial bee algorithm\, and others. Methodology\, converting evolutionary algorithms to the complex network will be introduced including demonstrations. The seminar then continues by explaining how evolutionary dynamics can be converted into so-called CML systems\, which are used to model spatiotemporal behavior (including chaotic one) and also will be explained its relation to complex networks. At the end will be demonstrated how we can control EAs dynamics using a feedback loop control scheme. The seminar is designed as a topic overview\, its structure\, results\, and content are based on our previous research\, journal publications\, keynotes\, and tutorials and reflect the latest progress in that field.
URL:https://datascience.unifi.it/index.php/event/recent-advances-and-progress-in-evolutionary-algorithms-and-its-dynamics/
LOCATION:Sala riunioni DINFO\, Via di Santa Marta 3\, Firenze\, Italy
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://datascience.unifi.it/wp-content/uploads/2019/11/Linfa_Universita_Firenze_DINFO_Logo.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20191205T120000
DTEND;TZID=Europe/Rome:20191205T133000
DTSTAMP:20260526T053423
CREATED:20191202T092509Z
LAST-MODIFIED:20191202T093203Z
UID:2418-1575547200-1575552600@datascience.unifi.it
SUMMARY:Lezione aperta DISEI Nobel 2019
DESCRIPTION:Title: Lezione aperta DISEI Nobel 2019\nSpeakers: Prof. Fabrizia Mealli (Director of the Florence Center for Data Science\, University of Florence) and Prof. Mario Biggeri (University of Florence)\nLocation: Building D6 Room 0.18 – Via delle pandette\, 9\n  \nDISEI is pleased to present the 2019 DISEI class on the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel.\nProf. Fabrizia Mealli and Prof. Mario Biggeri will present an overview of the main contributions of Abhijit Banerjee\, Esther Duflo and Michael Kremer who have received the 2019 “Nobel” prize in economics for their experimental approach to alleviating global poverty. \n 
URL:https://datascience.unifi.it/index.php/event/2418/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20191126T120000
DTEND;TZID=Europe/Rome:20191126T133000
DTSTAMP:20260526T053423
CREATED:20191122T123023Z
LAST-MODIFIED:20191122T123023Z
UID:2386-1574769600-1574775000@datascience.unifi.it
SUMMARY:Seminar @ DISEI : Il diritto On line
DESCRIPTION:Title: Blockchain\, smart contract e cryptovalute per le imprese \nSpeaker: Giovanni Brancalion Spadon (Foro di Venezia) \nLocation: Aula D5 001 – Polo delle Scienze Sociali – Viale delle Pandette 9
URL:https://datascience.unifi.it/index.php/event/seminar-disei-il-diritto-on-line/
LOCATION:D5 Via delle Pandette\, Via delle Pandette 9\, Firenze\, Italy
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20191104T101500
DTEND;TZID=Europe/Rome:20191104T120000
DTSTAMP:20260526T053423
CREATED:20191023T162604Z
LAST-MODIFIED:20191023T162641Z
UID:2177-1572862500-1572868800@datascience.unifi.it
SUMMARY:DISIA-DSG-DISEI seminar: Nello Cristianini
DESCRIPTION:Title: Living with Intelligent Machines\nSpeaker: Nello Cristianini (University of Bristol)\nLocation: Building D6 Room 1.18 – Via delle pandette\, 9\nABSTRACT \nThe way we build intelligent machines today involves two components: a (fairly) general learning algorithm\, and a (very) large set of training examples. These two elements are combined to create machine translation\, computer vision\, online recommendations\, spelling correction\, and so on. In many cases we know that the intended behaviour can be closely emulated\, but we have done away with modeling the mechanism that generates it\, replacing that with statistical correlations. As the training examples are often obtained “from the wild”\, they might contain information that we are not aware about\, including various cultural biases. If these biases enter in the statistical models\, they can be difficult to detect\, and become part of shaping the behaviour of the intelligent agent. As we train machines by exposing them to media content and other samples of human behaviour\, and these machines have the capability to emulate those behaviours\, it is important that we understand the biases present in the data: this is one case in which computational social sciences become an important element of AI design. Other cases include the automation of psychometrics\, and the risk of addiction. The social\, ethical and legal consequences of using modern-type of AI can be better understood and managed when we think about AI also from a social science perspective.  \nBIO \nNello Cristianini is Professor of Artificial Intelligence (AI) at the University of Bristol. His current research covers the large-scale analysis of media content (news and social media)\, using various AI methods\, the design of new AI methods\, their application to digital humanities and computational social science\, and the social impact of Big Data and AI technologies. Cristianini is the co-author of two widely known books in machine learning\, An Introduction to Support Vector Machines and Kernel Methods for Pattern Analysis\, as well as a book in bioinformatics\, Introduction to Computational Genomics. He is also a recipient of the Royal Society Wolfson Research Merit Award and a current holder of a European Research Council Advanced Grant. In 2014\, Thomson-Reuters included him in a list of the most influential computer scientists of the decade. Before joining the University of Bristol\, he has been a professor of statistics at the University of California\, Davis. Currently he is working on social and ethical implications of AI.
URL:https://datascience.unifi.it/index.php/event/disia-dsg-disei-seminar-nello-cristianini/
LOCATION:D6 Via delle Pandette 9\, Via delle Pandette 9\, Firenze\, Italy
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://datascience.unifi.it/wp-content/uploads/2019/10/medium-142795.jpg
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