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Functional Partial Least-Squares: Optimal Rates and Adaptation
Feb. 20, 2024, 5:46 a.m. | Andrii Babii, Marine Carrasco, Idriss Tsafack
stat.ML updates on arXiv.org arxiv.org
Abstract: We consider the functional linear regression model with a scalar response and a Hilbert space-valued predictor, a well-known ill-posed inverse problem. We propose a new formulation of the functional partial least-squares (PLS) estimator related to the conjugate gradient method. We shall show that the estimator achieves the (nearly) optimal convergence rate on a class of ellipsoids and we introduce an early stopping rule which adapts to the unknown degree of ill-posedness. Some theoretical and simulation …
abstract arxiv econ.em functional gradient least linear linear regression math.st regression show space squares stat.co stat.me stat.ml stat.th type
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