label switching technology is a flexible and high performance method for forwarding layer three packets that are mapped to layer two flows. each label switch router, lsr, needs a specific label for every flow, where the number of labels depends on the mapping and granularity of flows. data and control driven methods are the most significant and popular methods in label mapping policy. the above...

Multi-label classification is a generalization of binary classification where the task consists in predicting sets of labels. With the availability of ever larger datasets, the multi-label setting has become a natural one in many applications, and the interest in solving multi-label problems has grown significantly. As expected, deep learning approaches are now yielding state-of-the-art perform...

electron paramagnetic resonance (epr) spectroscopy, also known as electron spin resonance(esr) especially among physicists, is a strong and versatile spectroscopic method forinvestigation of paramagnetic systems, i.e. systems like free radicals and most transition metalions, which have unpaired electrons. the sensitivity and selectivity of epr are notable andintriguing as compared to other spec...

labeling theory is one of the most famous theories in criminology domain. the pivots of this theory consist of the role of power owners in definition of crime and determination of offender, effects of labeling and solutions for prevention of entering label. with study the pivots of labeling theory in islamic sources, we observe that however there is no similarity between religious bases and bas...

In multi-label learning, an example is represented by a descriptive feature associated with several labels. Simply considering labels as independent or correlated is crude; it would be beneficial to define and exploit the causality between multiple labels. For example, an image label ‘lake’ implies the label ‘water’, but not vice versa. Since the original features are a disorderly mixture of th...

Protein-protein interaction (PPI) networks are naturally viewed as infrastructure to infer signalling pathways. The descriptors of signal events between two interacting proteins such as upstream/downstream signal flow, activation/inhibition relationship and protein modification are indispensable for inferring signalling pathways from PPI networks. However, such descriptors are not available in ...

The Web offers a corpus of over 100 million tables [6], but the meaning of each table is rarely explicit from the table itself. Header rows exist in few cases and even when they do, the attribute names are typically useless. We describe a system that attempts to recover the semantics of tables by enriching the table with additional annotations. Our annotations facilitate operations such as sear...

With ever expanding size of the web, sizes of graphs with semantic relationships are growing very rapidly. The semantic relationships are typically presented as edge-labeled graphs where nodes are the entities and the edge label signifies the relationships between the two entities. RDF graphs are an example of such graphs. Pure reachability queries on these graphs do not give any information ab...

I have no financial relationships to disclose. I will not discuss off label use and/or investigational use in my presentation. research in constraint-induced movement therapy for children with unilateral cerebral palsy: an expert consensus.

Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels). To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR). MLC-LRR firstly utiliz...