NIPS 2011 Domain Adaptation Workshop: History Dependent Domain Adaptation
Domain Adaptation Workshop: Theory and Application at NIPS 2011
Invited Talk: History Dependent Domain Adaptation by Allen Lavoie
We study a novel variant of the domain adaptation problem, in which the loss function on test data changes due to dependencies on prior predictions. One important instance of this problem area occurs in settings where it is more costly to make a new error than to repeat a previous error. We propose several methods for learning effectively in this setting, and test them empirically on the real-world tasks of malicious URL classification and adversarial advertisement detection.