Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Background: Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query seq...
Ji Woong Kim, Yongju Ahn, Kichan Lee, Sung-Hee Par...
Integrating information in multiple natural languages is a challenging task that often requires manually created linguistic resources such as a bilingual dictionary or examples of...
— In recent years, the research community introduced various methods for processing skyline queries in multidimensional databases. The skyline operator retrieves all objects bein...