Události[VGSIT] Linear Programming Relaxation Approach to Discrete Energy MinimizationFIT VUT v Brně 12.4.2016 The next speaker in VGSIT series will be Tomáš Werner. The talk will be given on Tuesday, April 12 at 2pm in room A113. Title: Linear Programming Relaxation Approach to Discrete Energy Minimization Abstract: Discrete energy minimization consists in minimizing a function of many discrete variables that is a sum of functions, each depending on a small subset of the variables. This is also known as MAP inference in graphical models (Markov random fields) or weighted constraint satisfaction. Many successful approaches to this useful but NPcomplete problem are based on its natural LP relaxation. I will discuss this LP relaxation in detail, along with algorithms able to solve it for very large instances, which appear e.g. in computer vision. In particular, I will discuss in detail a convex message passing algorihtm, generalized minsum diffusion. Tomáš Werner works as a researcher at the Center for Machine Perception, Faculty of Electrical Engineering, Czech Technical University, where he also obtained his PhD degree. In 20012002 he worked as a postdoc at the Visual Geometry Group, Oxford University, U.K. In the past, his main interest was multiple view geometry and threedimensional reconstruction in computer vision. Today, his interest is in machine learning and optimization, in particular graphical models. He is a (co)author of more than 70 publications, with 350 citations in WoS. All are cordially invited.
