AutoML 2020: 7th ICML Workshop on Automated Machine Learning |
Website | http://icml2020.automl.org |
Submission link | https://easychair.org/conferences/?conf=automl2020 |
Abstract registration deadline | May 20, 2020 |
Submission deadline | May 20, 2020 |
+++ We have extended the submission deadline to May 20th (Anywhere on earth) +++
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. Hence, 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.
Topics
We invite submissions on the topics of:
- Model selection, hyper-parameter optimization, and model search
- Neural architecture search
- Meta-learning and transfer learning
- Bayesian optimization for AutoML
- Evolutionary algorithms for AutoML
- Multi-fidelity optimization
- Predictive models of performance
- Automatic feature extraction / construction
- Automatic data cleaning
- Automatic generation of workflows / workflow reuse
- Automatic problem "ingestion" (from raw data and miscellaneous formats)
- Automatic feature transformation to match algorithm requirements
- Automatic acquisition of new data (active learning, experimental design)
- Automatic report generation (providing insight on automatic data analysis)
- Automatic selection of evaluation metrics / validation procedures
- Automatic selection of algorithms under time/space/power constraints
- Automatic construction of fair and unbiased machine learning models
- Automation of semi-supervised and unsupervised machine learning
- Demos of existing AutoML systems
- Robustness of AutoML systems (w.r.t. Randomized algorithms, data, hardware etc.)
- Human-in-the-loop approaches for AutoML
- Learning to learn new algorithms and strategies
- Hyperparameter agnostic algorithms
Submission Format
We welcome submissions up to 6 pages in JMLR Workshop and Proceedings format (plus 10 pages for references and appendix). All accepted papers will be presented as posters. We will invite the 2-3 best papers for an oral plenary presentation. Unless indicated by the authors, we will provide PDFs of all accepted papers on http://icml2020.automl.org/. There will be no archival proceedings. For submission details please see the submission page.
Remark on COVID-19:
We are in contact with the ICML organizers about how the conference and workshops will be organized as ICML will be a virtual conference. We will inform you as soon as possible.
Confirmed Keynote Speakers:
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Alex Smola (Director, Amazon Web Services)
-
Mihaela van der Schaar (Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge)
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Neil Lawrence (DeepMind Professor of Machine Learning at the University of Cambridge and visiting Professor at the University of Sheffield)
Location:
The 7th ICML AutoML workshop will be co-located with the 37th International Conference on Machine Learning (ICML 2020) in Vienna, Australia, and will take place on July 17th or 18th.
Important Dates:
Submission Deadline: April 23rd (Anywhere on earth)
Author Notification: May 25th (Anywhere on earth)
Further information
We provide up-to-date information on http://icml2020.automl.org/