Titlebook: Similarity-Based Pattern Recognition; Second International Edwin Hancock,Marcello Pelillo Conference proceedings 2013 Springer-Verlag Berli

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Pattern Learning and Recognition on Statistical Manifolds: An Information-Geometric Review,tal statistical pattern recognition problems. We then concisely review the main statistical distances and report a novel versatile family of divergences. Depending on their intrinsic complexity, the statistical patterns are learned by either atomic parametric distributions, semi-parametric finite mi

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Data Analysis of (Non-)Metric Proximities at Linear Costs,ta objects and to cover domain specific data properties. Lacking an underlying vector space, data are given as pairwise (dis-)similarities. The few available methods for such data do not scale well to very large data sets. Kernel methods easily deal with . matrices, also at large scale, but costly t

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不朽中國(guó)

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Break and Conquer: Efficient Correlation Clustering for Image Segmentation,pixels and a local information is extracted for each pair of spatially adjacent superpixels. The global optimization problem is then cast as correlation clustering which is known to be NP hard. This study demonstrates that in many cases, finding the exact global solution is still feasible by exploit