Please find enclosed the announcement of the 11th edition of the ABS (Applied Bayesian Statistics) summer school. Like this year, the 2014 school will be held in the magnificent Villa del Grumello, in Como (Italy), on the Lake Como shore. Guido Consonni and Fabrizio Ruggeri ABS14 Directors -------------------------------------------------------------- ******************************* * ABS14 * ******************************* Applied Bayesian Statistics School APPLIED BAYESIAN NONPARAMETRICS June, 16 - 20, 2014 - Villa del Grumello, Como, Italy Lecturers 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 The conference webpage is >>>> www.mi.imati.cnr.it/conferences/abs14.html <<<< Registration will start after January, 1st, 2014 and details on programme and accommodations will be provided early next year. The conference room allows only for a very limited number of participants (max. 35). Interested people are invited to contact the ABS14 Secretariat at abs14@mi.imati.cnr.it --------------------- COURSE OUTLINE ---------------------------------------- The school will make use of lectures, practical sessions, software demonstrations with Matlab/Octave, 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. The topics covered by the lecturers will be: - General introduction and motivation: Why Bayesian nonparametrics? - Dirichlet process mixtures, Chinese restaurant process, stick-breaking construction - Computational methods for Dirichlet process mixtures - Models beyond the Dirichlet process: Completely random measures, Pitman-Yor and Beta-Bernoulli processes - Applications to natural language processing - Applications to network analysis - Hierarchical Bayesian nonparametric models - Applications to topic modeling