When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Selecting the right parties to interact with is a fundamental problem in open and dynamic environments. The problem is exemplified when the number of interacting parties is high a...
We explore the use of the landing page content in sponsored search ad selection. Specifically, we compare the use of the ad’s intrinsic content to augmenting the ad with the wh...
Yejin Choi, Marcus Fontoura, Evgeniy Gabrilovich, ...