ABS14 - 2014 Applied Bayesian Statistics School

APPLIED BAYESIAN NONPARAMETRICS

Villa del Grumello, Como, Italy

June, 16-20, 2014





Grumello




ATTENTION !!

  Registrations  to ABS14 are closed!.





NEW !!

The detailed program of ABS14 and the list of participants are now available on-line.





ABS SCHOOLS

The Applied Bayesian Statistics summer school has been running since 2004. From 2012 it is organized by

  • IMATI CNR
    Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche
  • Dipartimento di Scienze Statistiche
    UniversitÓ Cattolica, Milano
  • This year the school is organized in cooperation with  Centro di Cultura Scientifica "Alessandro Volta"

    The school aims to present state-of-the-art Bayesian applications, inviting leading experts in their field. Each year a different topic is chosen. Past editions were devoted to Gene Expression Genomics, Decision Modelling in Health Care, Spatial Data in Environmental and Health Sciences, Bayesian Methods and Econometrics, Bayesian Decision Problems in Biostatistics and Clinical Trials, Bayesian Methodology for Clustering, Classification and Categorical Data Analysis, Bayesian Machine Learning with Biomedical Applications, Hierarchical Modeling for Environmental Processes, Stochastic Modelling for Systems Biology and Bayesian Methods for Variable Selection with Applications to High-Dimensional Data.


    TOPIC AND LECTURERS

    The topic chosen for the 2014 school is Applied Bayesian Nonparametrics.  The lecturers are:

    Professor  Michael Jordan,  Department of Electrical Engineering and Computer Science and  Department of Statistics at the University of California, Berkeley, USA.

     Professor Francois Caron, Department of Statistics, University College Oxford, UK.


    COURSE DESCRIPTION

    Bayesian nonparametrics is the branch of Bayesian analysis in which the prior is specified not in terms of a distribution with a fixed set of parameters, but rather via a stochastic process---an infinite collection of random variables.  The infinite nature of nonparametric models creates both opportunities and challenges.  The opportunities are those of flexibility and robustness---nonparametric approaches supply open-ended sets of degrees of freedom to models, allowing new phenomena to be captured as data accrue, and they often require weaker a priori assumptions than classical parametric models.  On the other hand, the challenges are those of exerting statistical control on the degrees of freedom so that models find signal rather than noise and those of finding effective computational procedures for manipulating stochastic processes under operations of conditioning and marginalization.
    Much of the recent growth in interest in Bayesian nonparametrics is driven by the needs of applications.  In particular, data in emerging domains such as document modeling, social network analysis, image processing and natural language processing present many of the features that Bayesian nonparametrics aims to capture.  Accordingly, our development of the field will be application-centric, with models motivated by real-world problems.

    The school will make use of lectures, practical sessions, software demonstrations, informal discussion sessions and presentations of research projects by school participants. The slides and background reading material will be distributed to the students before the start of the course.

    COURSE OUTLINE


    The course will involve both lectures and practical sessions with Matlab/Octave.



    INTENDED PARTICIPANTS AND PREREQUISITES


    The prerequisites for this course will include basic knowledge of algebra and calculus, probability, statistical modelling, and data analysis. Some background on Bayesian analysis and the basics of MCMC is desiderable. This course will be beneficial to graduate students, post-docs and researchers both from academia, government, and industry whose area of activity is Statistics.


    READING

    SOFTWARE

    Participants are expected to bring their own laptop with recent versions of  Matlab or Octave, in order to actively participate in the practical sessions.

    The Octave language is quite similar to Matlab so that most programs are easily portable. Octave is distributed under the terms of the GNU General Public License
    All information about GNU Octave can be found here.


    LOCATION AND SCHEDULE

    The 2014 school will be held at Villa del Grumello, a magnificent villa located in the city of Como, along the Lake Como shoreline.

    Please note that the number of available places is limited.

    The school will start on Monday,  June,16th,  and it will end on Friday, June, 20st
    Welcome buffet and farewell dinner are planned on June 16th and 19th, respectively, as well as two lunches on June, 17th and 19th. Participants will have a free afternoon on June, 18th.



    FEES

    The registration fees (for payments before April, 1th, 2014) are:

  • EUR 400 (22% VAT included) for students and postdocs
  • EUR 550 (450.82 + 22% VAT) for people from academic and non-profit organisations
  • EUR 900 (737.70 + 22% VAT) for all the others
  • including teaching materials, two lunches, welcome cocktail and farewell dinner .

    For late payments (after April, 1th, 2014) please add 60 euros (49.18 + 22% VAT).


    Meals, snacks and drinks are available nearby and they are the participants' responsibility.


    INFORMATION