Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
Labeling nodes in a network is an important problem that has seen a growing interest. A number of methods that exploit both local and relational information have been developed fo...
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
Abstract. In order to exploit the dependencies in relational data to improve predictions, relational classification models often need to make simultaneous statistical judgments abo...