Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...
Metric learning is a fundamental problem in computer vision. Different features and algorithms may tackle a problem from different angles, and thus often provide complementary inf...
Bo Wang, Jiayan Jiang, Wei Wang 0028, Zhi-Hua Zhou...
We present a new approach to matching graphs embedded in R2 or R3 . Unlike earlier methods, our approach does not rely on the similarity of local appearance features, does not req...
Eduard Serradell, Przemyslaw Glowacki, Jan Kybic, ...
—Graph visualization has been widely used to understand and present both global structural and local adjacency information in relational datasets (e.g., transportation networks, ...
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...