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Existing surface reconstruction methods only work for low-dimensional, mostly 2D or 3D, data. In real applications, high-dimensional data is difficult to interpret as it requires more dimensions to represent. As a dimension reduction method, manifold learning provides an explicit representation for the useful implicit information hidden in the original feature space. But the internal topological and...
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