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
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