Robust weights and designs for biased regression models: Least squares and generalized M-estimation

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Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation (2009, background): “Covariate shift is also naturally induced in selective sampling or active learning scenarios [10, 8, 30 , 18, 23].”
Importance weighted active learning (2008, background): “Wiens [17] investigated linear regression in the presence o f a contaminating signal added into the target variable.”
Covariate Shift Adaptation by Importance Weighted Cross Validation (2007, methodology): “For linear regression, IWLS-based active learning methods that focus on minimizing the variance of the estimator have been developed (Wiens, 2000; Sugiyama, 2006a).”
Dataset Shift in Machine Learning (2009, methodology): “On the other hand, when selecting the training input density with existing active learning methods, the model must have been fixed [Fedorov, 1972; MacKay, 1992b; Cohn et al., 1996; Fukumizu, 2000; Wiens, 2000; Kanamori and Shimodaira, 2003; Sugiyama, 2006].”