General regularization in covariate shift adaptation
General regularization in covariate shift adaptation
Sample reweighting is one of the most widely used methods for correcting the error of least squares learning algorithms in reproducing kernel Hilbert spaces (RKHS), which is caused by future data distributions that are different from the training data distribution. In practical situations, the sample weights are determined by values …