We consider probabilistic constrained linear programs with general distributions for the uncertain parameters. These problems generally involve non-convex feasible sets. We develo...
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....
In this paper we use a Unified Relationship Matrix (URM) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks...
Wensi Xi, Edward A. Fox, Weiguo Fan, Benyu Zhang, ...
Most classification algorithms receive as input a set of attributes of the classified objects. In many cases, however, the supplied set of attributes is not sufficient for creatin...
Through a defined research process we designed objects that behave and respond in specific ways and are part of a networked system that emphasizes autonomous and flocking behavior...