Machine learning has achieved considerable successes in recent years, but this success often relies on human experts, who construct appropriate features, design learning architectures, set their hyperparameters, and develop new learning algorithms. Driven by the demand for off-the-shelf machine learning methods from an ever-growing community, the research area of AutoML targets the progressive automation of machine learning aiming to make effective methods available to everyone. The workshop targets a broad audience ranging from core machine learning researchers in different fields of ML connected to AutoML, such as neural architecture search, hyperparameter optimization, meta-learning, and learning to learn, to domain experts aiming to apply machine learning to new types of problems.
We invite submissions on the topics of:
We welcome submissions up to 6 pages in JMLR format (+ references). We strongly encourage attachments of code to foster reproducibility; reproducibility of results and easy availability of code will be taken into account in the decision making process. All accepted papers will be presented as posters. We may invite the best 2-3 papers for an oral plenary presentation. Unless indicated by the authors, we will provide PDFs of all accepted papers on http://icml2019.automl.org/. There will be no archival proceedings. For submission details please see the submission page.
The 6th ICML AutoML workshop will be co-located with the 36th International Conference on Machine Learning (ICML 2019) in Long Beach, CA, USA and will take place on June 14 . Please check the practical information page for further information.