Learning from Dependent Observations

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Security analysis of online centroid anomaly detection (2010, background): “Furthermore, even the recent work on learning with differing training and test distributions (Sugiyama et al., 2007) is not necessarily appropriate for adversarial input, as in the latter case one must account for a specific worst-case difference.”