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Research questionHow can online functional PCA reduce streaming multidimensional data while retaining smooth, orthogonal components and uncertainty estimates?Multidimensional functional streams arrive continuously, making repeated batch analysis costly as new observations accumulate. The estimated components must remain smooth and orthogonal while their uncertainty and smoothing choices are updated over time.
Machine Learning
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Online Learning of Functional Principal Component Analysis for Multidimensional Functional DataThe source presents an online functional principal component analysis framework using tensor-product splines, penalization on a Stiefel manifold, Riemannian stochastic optimization, iterative averaging, and rolling block validation for smoothing selection. It derives asymptotic normality and pointwise confidence intervals, with evidence from simulations and real-world applications.research paper · Sep 3, 2026
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