A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Hierarchical categorization is a powerful and convenient method so that it is commonly used in various areas, such as ontologies. Although each hierarchy is useful, there are probl...
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...
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
d abstract) John Kececioglu and Dean Starrett Department of Computer Science The University of Arizona Tucson AZ 85721, USA A basic computational problem that arises in both the...