Convergence Analysis of Nystr\"om Subsampling in Covariate Shift Adaptation for Misspecified case (opens in new tab)

This paper investigates convergence properties of regularized Nystr\"om subsampling applied to the unsupervised domain adaptation problem under covariate shift. We focus on the low-smoothness (misspecified) case where the target function lies outside the reproducing kernel Hilbert space. By combining Tikhonov regularization with Nystr\"om projection onto a subsampled subspace, we obtain upper bounds on the excess risk that hold with high probabi...