Ellipsoid fitting with the Cayley transform.


Melikechi, O; Dunson, DB


We introduce Cayley transform ellipsoid fitting (CTEF), an algorithm that uses the Cayley transform to fit ellipsoids to noisy data in any dimension. Unlike many ellipsoid fitting methods, CTEF is ellipsoid specific, meaning it always returns elliptic solutions, and can fit arbitrary ellipsoids. It also significantly outperforms other fitting methods when data are not uniformly distributed over the surface of an ellipsoid. Inspired by growing calls for interpretable and reproducible methods in machine learning, we apply CTEF to dimension reduction, data visualization, and clustering in the context of cell cycle and circadian rhythm data and several classical toy examples. Since CTEF captures global curvature, it extracts nonlinear features in data that other machine learning methods fail to identify. For example, on the clustering examples CTEF outperforms 10 popular algorithms.


Melikechi, Omar, and David B. Dunson. “Ellipsoid fitting with the Cayley transform.” IEEE Transactions on Signal Processing : A Publication of the IEEE Signal Processing Society 72 (January 2024): 70–83. https://doi.org/10.1109/tsp.2023.3332560.
Cover:IEEE Transactions on Signal Processing

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