We would like to thank all reviewers for your helpful suggestions. In what follows we answer your questions to help clarify the notations and experiments. "motivation not clear": G-SSL and specifically label propagation used to be an important semi-supervised learning We will try to include more real-world examples in the revised version. ": following the standard notations, we use The feature matrix is composed of labeled part and unlabeled part. "Datasets not explained": we will add more descriptions of datasets in the next version.

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The empirical results are nice and the proposed method can be one of the candidates for the classification method for large datasets.

However, it is unrealistic to label all the object classes, thus making these supervised learning methods struggle to recognize objects which are unseen during training.

Neural Information Processing Systems http://nips.cc/

We consider the problem of estimating the mean of a set of vectors, which are stored in a distributed system.

The model proposed here enables proper uncertainty quantification of the causal effects thus allowing the definition of optimal experimental design strategies.