Resampling and averaging coordinates on data - Inria - Institut national de recherche en sciences et technologies du numérique
Pré-Publication, Document De Travail Année : 2024

Resampling and averaging coordinates on data

Résumé

We introduce algorithms for robustly computing intrinsic coordinates on point clouds. Our approach relies on generating many candidate coordinates by subsampling the data and varying hyperparameters of the embedding algorithm (e.g., manifold learning). We then identify a subset of representative embeddings by clustering the collection of candidate coordinates and using shape descriptors from topological data analysis. The final output is the embedding obtained as an average of the representative embeddings using generalized Procrustes analysis. We validate our algorithm on both synthetic data and experimental measurements from genomics, demonstrating robustness to noise and outliers.

Dates et versions

hal-04706757 , version 1 (23-09-2024)

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Andrew J. Blumberg, Mathieu Carriere, Jun Hou Fung, Michael A. Mandell. Resampling and averaging coordinates on data. 2024. ⟨hal-04706757⟩
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