Extraction of entities from ad creatives is an important problem that can benefit many computational advertising tasks. Supervised and semi-supervised solutions rely on labeled da...
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
One of the important challenges facing music information retrieval (MIR) of audio signals is scaling analysis algorithms to large collections. Typically, analysis of audio signals...
In this paper, we discuss a prototype application deployed at the U.S. National Science Foundation for assisting program directors in identifying reviewers for proposals. The appl...
We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it t...