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What is AutoML?

Machine learning is very successful, but its successes crucially rely on human machine learning experts, who select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. As the complexity of these tasks is often beyond non-experts, the rapid growth of machine learning applications has created a demand for off-the-shelf machine learning methods that can be used easily and without expert knowledge. We call the resulting research area that targets progressive automation of machine learning AutoML.

Please see the call for papers for areas of particular relevance to the workshop.

Confirmed invited speakers

• Chelsea Finn

• Zoubin Ghahramani

• Luc de Raedt

Organization

Co-chairs: Roman Garnett, Frank Hutter, Joaquin Vanschoren

Organizing committee: Pavel Brazdil, Rich Caruana, Christophe Giraud-Carrier, Isabelle Guyon, Balazs Kegl

Sponsorship

We are very thankful to our sponsors!