Abstract. We address the problem of joint feature selection in multiple related classification or regression tasks. When doing feature selection with multiple tasks, usually one c...
Paramveer S. Dhillon, Brian Tomasik, Dean P. Foste...
Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
—In this paper, we propose an integrated methodology for specifying AIN and switch-based features and analyzing their interactions in the AIN 0.1 framework. The specification of ...
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...