منابع مشابه
Fitting the Smallest Enclosing Bregman Ball
Finding a point which minimizes the maximal distortion with respect to a dataset is an important estimation problem that has recently received growing attentions in machine learning, with the advent of one class classification. We propose two theoretically founded generalizations to arbitrary Bregman divergences, of a recent popular smallest enclosing ball approximation algorithm for Euclidean ...
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We develop a simple combinatorial algorithm for computing the smallest enclosing ball of a set of points in high dimensional Euclidean space. The resulting code is in most cases faster (sometimes significantly) than recent dedicated methods that only deliver approximate results, and it beats off-the-shelf solutions, based e.g. on quadratic programming solvers. The algorithm resembles the simple...
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This technical report deals with the smallest enclosing ball problem subject to probabilistic data. In our setting, any of n points may not or may occur at one of finitely many locations, following its own discrete probability distribution. The objective is therefore considered to be a random variable and we aim at finding a center minimizing the expected maximum distance to the points accordin...
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ژورنال
عنوان ژورنال: Communications in Information and Systems
سال: 2012
ISSN: 1526-7555,2163-4548
DOI: 10.4310/cis.2012.v12.n3.a1