Overfitting and Small Sample Statistics (Salakhutdinov, 2011)

Domain Adaptation Workshop: Theory and Application at NIPS 2011 Invited Talk: Overfitting and Small Sample Statistics by Ruslan Salakhutdinov Abstract: We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample domains, but where we have many samples in each domain. Our goal is to generalize to a new domain. For example, we may want to learn a similarity function using on