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Learning Submanifolds for Subsequent Inference on Random Dot Product Graphs, Part 1: Theory
We propose a framework for restricted inference on random dot product graphs whose latent positions lie on an unknown low-dimensional support manifold. For general decision problems, we propose semisupervised decision rules that use auxiliary data to learn the support manifold. Specifically, our rul
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