Author

M. Trosset

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#machine learning Review May 2025

Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction

The various kernel methods that are encountered are surveyed and it is shown that each can be derived from one or the other of two competing strategies: *projection* or *restricted reconstruction*.

M. Trosset, Kaiyi Tan, M. Tang et al. · Journal of Computational And... · 0 citations

#machine learning Preprint Sep 2026

Learning Submanifolds for Subsequent Inference on Random Dot Product Graphs, Part 1: Theory

It is shown that, as the auxiliary sample size increases, the risk of the semisupervised rule converges to the risk of an oracle rule that relies on the maximal amount of low-dimensional Euclidean structure that can be extracted from the support manifold.

M. Trosset, Carey E. Priebe · 0 citations