We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
In this paper we propose a novel non-rigid volume registration based on discrete labeling and linear programming. The proposed framework reformulates registration as a minimal path...
Ben Glocker, Nikos Komodakis, Nikos Paragios, Geor...
Building a model using machine learning that can classify the sentiment of natural language text often requires an extensive set of labeled training data from the same domain as t...
Abstract. In this paper we investigate the problem of exploiting multiple sources of information for object recognition tasks when additional modalities that are not present in the...
Abstract. Using a discovery-with-models approach, we study the relationships between novice Java programmers’ experiences of confusion and their achievement, as measured through ...
Diane Marie C. Lee, Ma. Mercedes T. Rodrigo, Ryan ...