Workshop topics of interest include, but are not limited to the following:

New ensemble methods raised from new real world supervised and unsupervised learning problems

Application of ensemble methods in various branches of science and technology: bioinformatics, medical informatics, computer security, economics, ecology, meteorology and weather forecast, image analysis and signal processing, satellite image analysis.

Multi-class, multi-label, multi-path ensemble methods for hierarchically structured taxonomies.

Fusion of multiple-source/multi-sensor data

Unsupervised ensemble methods for discovering structures in unlabeled real data

Unsupervised ensemble approaches to assess the reliability/validity of clusters discovered in real data

Combination techniques and methods to generate multiple base learners from different features and data

Dynamic member selection for including into an ensemble

Heterogeneous ensembles of base learners

Variants of re-sampling-based methods (bagging, boosting)

Ensemble methods for supervised multi-class classification and regression

Supervised and unsupervised ensemble methods for structured domains

Ensemble methods for adaptive incremental learning