Topics covered by this workshop include but are not limited to:

• Supervised learning (Single- and multi-label classification)

• Unsupervised learning

• Semi-supervised learning

• Active learning

• Deep learning

• Reinforcement learning

• Regression and approximation 

• Data mining and knowledge discovery

• Ensemble methods (bagging, boosting, model fusion techniques, etc)

• Feature selection and reduction 

• Incremental and online learning 

• Concept drift and shift in data streams

• Adaptive data pre-processing

• Real world applications such as:

1. Big Data

2. Cloud computing

3. Modelling and system identification

4. Time-Series prediction and forecasting 

5. Quality control systems and condition monitoring

6. Fault detection, isolation, identification and diagnosis

7. Predictive maintenance and prognostics 

8. Internet

9. Decision support systems

10. (Bio)Medical applications 

11. Robotics, intelligent transport and advanced manufacturing

12. Multi-media applications

13. Social networksAuthors