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Subspace segmentation is the task of segmenting data lying on multiple linear subspaces. Its applications in computer vision include motion segmentation in video, structure-from-motion, and image clustering. In this work, we describe a novel approach for subspace segmentation that uses probabilistic inference via a message-passing algorithm. We cast the subspace segmentation problem as that of choosing...
The Estimation of Distribution Algorithms (EDAs) is a novel class of evolutionary algorithms which is motivated by the idea of building probabilistic graphical model of promising solutions to represent linkage information between variables in chromosome. Through learning of and sampling from probabilistic graphical model, new population is generated and optimization procedure is repeated until the...
Message-passing methods provide powerful approximation algorithms for problems that can be formulated in terms of (probabilistic) graphical models. These methods find applications in statistical physics, inference, and combinatorial optimization. Sudoku, a popular number puzzle, is a simple optimization problem that message-passing algorithms can help solve. Therefore, Sudoku is an ideal vehicle to...
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