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stat.ML2024
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm
Zhu Li, Dimitri Meunier, Mattes Mollenhauer +1
We present the first optimal rates for infinite-dimensional vector-valued ridge regression on a continuous scale of norms that interpolate between and the hypothesis space, w…
stat.ML2024
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
Dimitri Meunier, Zikai Shen, Mattes Mollenhauer +2
We study theoretical properties of a broad class of regularized algorithms with vector-valued output. These spectral algorithms include kernel ridge regression, kernel principal co…