Math @ Duke
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Publications [#265012] of Guillermo Sapiro
Papers Published
- Haro, G; Randall, G; Sapiro, G, Stratification learning: Detecting mixed density and dimensionality in high dimensional point clouds,
Advances in Neural Information Processing Systems
(December, 2007),
pp. 553-560, ISSN 1049-5258
(last updated on 2025/02/02)
Abstract: The study of point cloud data sampled from a stratification, a collection of manifolds with possible different dimensions, is pursued in this paper. We present a technique for simultaneously soft clustering and estimating the mixed dimensionality and density of such structures. The framework is based on a maximum likelihood estimation of a Poisson mixture model. The presentation of the approach is completed with artificial and real examples demonstrating the importance of extending manifold learning to stratification learning.
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