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Parametric Embedding for Class Visualization
Neural Computation, no. 9 (2007): 2536-2556
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摘要
We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under t...更多
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