Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Nearest neighbor queries are important in many settings, including spatial databases (Find the k closest cities) and multimedia databases (Find the k most similar images). Previou...
The objective of this work is to define procedures to improve spatial resolution of SRTM data and to evaluate their applicability in the Serra Negra region, in the district of Pat...
T. Bernardes, I. Gontijo, H. Andrade, T. G. C. Vie...
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...