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• W2105280352 abstract "We consider the problem of fitting a convex piecewise-linear function, with some specified form, to given multi-dimensional data. Except for a few special cases, this problem is hard to solve exactly, so we focus on heuristic methods that find locally optimal fits. The method we describe, which is a variation on the K-means algorithm for clustering, seems to work well in practice, at least on data that can be fit well by a convex function. We focus on the simplest function form, a maximum of a fixed number of affine functions, and then show how the methods extend to a more general form." @default.
• W2105280352 created "2016-06-24" @default.
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• W2105280352 date "2008-03-25" @default.
• W2105280352 modified "2023-10-10" @default.
• W2105280352 title "Convex piecewise-linear fitting" @default.
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• W2105280352 doi "https://doi.org/10.1007/s11081-008-9045-3" @default.
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