Multi-instance multi-label learning (MIML) refers to the
learning problems where each example is represented by a
bag/collection of instances and is labeled by multiple labels.
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Rong Jin (Michigan State University), Shijun Wang...
The design and implementation of the reconstruction system in medical X-ray imaging is a challenging issue due to its immense computational demands. In order to ensure an efficien...
Holger Scherl, Stefan Hoppe, Markus Kowarschik, Jo...
: Heterogeneous wireless sensor networks represent a challenging programming environment. Servilla addresses this by offering a new middleware framework that provides service provi...
The WHO Collaborating Centre for International Drug Monitoring in Uppsala, Sweden, maintains and analyses the world's largest database of reports on suspected adverse drug re...
Pattern matching over event streams is increasingly being employed in many areas including financial services, RFIDbased inventory management, click stream analysis, and electroni...
Jagrati Agrawal, Yanlei Diao, Daniel Gyllstrom, Ne...