Learning in Graphical Models Rutilius Taurus Aemilianus Audience: Undergraduates and graduates in

Audience: Undergraduates and graduates in electrical engineering and physics schools

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Learning in Graphical Models Rutilius Taurus Aemilianus Audience: Undergraduates and graduates inIn the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the