Partial Label Learning (PLL) aims to train a classifier when each training instance is associated with set of candidate labels, among which only one correct but not accessible during the phase. The common strategy dealing such ambiguous labeling information disambiguate label sets. Nonetheless, existing methods ignore disambiguation difficulty instances and adopt single-trend mechanism. former ...

• The discriminative visual embedding preserves the information of image features by separating inter-classes and clustering intra-classes with a margin. semantic acts as pivot regularization to ensure cooperated structures representative utilizing relations between classes. Extensive experimental evaluation on multiple datasets, including large scale ImageNet shows that proposed model performs...

This article describes the Mobility-aware Tag-based Cooperation (MaTaCo) approach to cooperation enforcement in mobile environments or MANETs. The MaTaCo approach models individual nodes in mobile environments or MANETs as adaptive tag-based agents capable of adapting their cooperation to changing mobile environment. In contrast to existing work on tag-based cooperation, MaTaCo provides a mobil...

This report identifies mechanisms and techniques for the efficient cooperation among heterogeneous radio access networks (RANs), with focus on the cooperation between the WINNER RAN and legacy RANs (GSM/GPRS/UMTS and IEEE 802.11, 802.16, and DVB). The report has two main parts. The first part is an initial description of cooperation architectures and coupling schemes, later to be analyzed for o...