Whitening transformations and orthogonality of random variables; today's reading.

preconditioning today-i-read whitening-transformations

  1. Agnan Kessy, Alex Lewin, and Korbinian Strimmer, “Optimal Whitening and Decorrelation,” The American Statistician, vol. 72, no. 4, pp. 309–314, Oct. 2018, doi: 10.1080/00031305.2016.1277159. [Online]. Available at: https://doi.org/10.1080/00031305.2016.1277159. [Accessed: September 8, 2023]

    tl;dr: Covers ‘whitening’, linear transforms that convert random vectors to another random vector, where the new random vector has covariance equal to the identity matrix. Five types discussed: zero-phase components analysis (ZCA) or Mahalanobis whitening, PCA whitening, Cholesky whitening, ZCA-cor, and PCA-cor. ZCA whitening is used in paper ‘CamP: Camera Preconditioning for Neural Radiance Fields’, Park et al. 2023. ‘Whitening’ is equivalent to the term ‘sphering’.

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