Recent advances in hardware technology have facilitated new ways of collecting data continuously, giving rise to data streams. In many applications, the volume of such data is so large that it may be impossible to store the data on disk. Furthermore, even when the data can be stored, the volume of incoming data may be so large as to be impossible to process. Internet traffic, financial transactions related to securities and options, and sensor-based data collection related to continuous physical observations such as temperature, pressure, human EEG signals or vibrations in manufacturing industries, are typical data streaming scenarios. Thus, the development of machine learning algorithms becomes significantly challenging in this context.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Full papers in the ECAI format
• Deathline is March 29, 2020

List of Topics

• Machine Learning
• Data streams

Committees

Organizing committee

• Concha Bielza
• Joao Gama
• Pedro Larrañaga

Venue

The conference will be held in Santiago de Compostela

Contact

All questions about submissions should be emailed to mcbielza@fi.upm.es, jgama@fep.up.pt or pedro.larranaga@fi.upm.es