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Conditional Manifold Learning

11/26/2021

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by Anh Tuan Bui, et al.

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This paper addresses a problem called "conditional manifold learning", which aims to learn a low-dimensional manifold embedding of high-dimensional data, conditioning on auxiliary manifold information. This auxiliary manifold information is from controllable or measurable conditions, which are ubiquitous in many science and engineering applications. A broad class of solutions for this problem, conditional multidimensional scaling (including a conditional ISOMAP variant), is proposed. A conditional version of the SMACOF algorithm is introduced to optimize the objective function of conditional multidimensional scaling.

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