BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Phase Transitions of Generalized Sparse Gaussian Prior in Bayesian
Image Modeling
DTSTART;VALUE=DATE-TIME:20170315T150000Z
DTEND;VALUE=DATE-TIME:20170315T170000Z
DTSTAMP;VALUE=DATE-TIME:20190524T205936Z
UID:indico-event-13103@agenda.infn.it
DESCRIPTION:\n In the Bayesian image modeling\, a generalized sparse Ga
ussian prior probability distribution is one of very useful priors. Our p
rior includes sparsity in each interaction term between every pair of nei
ghbouring nodes in Markov random fields. The sparsity is based on the $L_
p$ norm ($0