Before revision:  Finally, TR or interpolation being a building block of several algorithms, we show how the proposed estimators can be easily adapted to avoid expensive intermediate steps in well-known algorithms such as generalized semi-supervised learning, label propagation, Newton's method and iteratively reweighted least square .
After revision:  Finally, TR or interpolation being a building block of several algorithms, we show how the proposed estimators can be easily adapted to avoid expensive intermediate steps in well-known algorithms such as generalized semi-supervised learning, label propagation, Newton's method and iteratively reweighted least squares .