CFP: ICML/IJCAI-ECAI 2018 Workshop on Automatic Machine Learning (AutoML 2018)

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Christophe Giraud-Carrier

Mar 30, 2018, 10:42:58 AM3/30/18
to Metalearning and Algorithm Selection


The ICML/IJCAI-ECAI 2018 Workshop on Automatic Machine Learning (AutoML 2018)

Collocated with the Federated AI Meeting (including ICML, IJCAI, AAMAS, and ICCBR) in Stockholm, July 13, 14, or 15 (TBD), 2018



Important Dates:

Submission deadline: 23 May 2018, 11:59pm UTC-12 (May 23 anywhere in the world)

Notification: 9 June 2018


Workshop topic:

Machine learning has been very successful, but its successes rely on human machine learning experts to define the learning problem, select, collect and preprocess the training data, choose appropriate ML architectures (deep learning, random forests, SVMs, etc) and their hyperparameters, and finally evaluate the suitability of the learned models for deployment. 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 are more bullet-proof and can be used easily without expert knowledge. We call the resulting research area that targets progressive automation of machine learning AutoML.

AutoML aims to automate many different stages of the machine learning process, and encourages contributions in any of the following (or related) areas:

- Model selection, hyper-parameter optimization, and model search

- Neural architecture search

- Meta learning and transfer learning

- Automatic feature extraction / construction

- Demonstrations (demos) of working AutoML systems

- Automatic generation of workflows / workflow reuse

- Automatic problem "ingestion" (from raw data and miscellaneous formats)

- Automatic feature transformation to match algorithm requirements

- Automatic detection and handling of skewed data and/or missing values

- Automatic acquisition of new data (active learning, experimental design)

- Automatic report writing (providing insight on automatic data analysis)

- Automatic selection of evaluation metrics / validation procedures

- Automatic selection of algorithms under time/space/power constraints

- Automatic prediction post-processing and calibration

- Automatic leakage detection

- Automatic inference and differentiation

- User interfaces and human-in-the-loop approaches for AutoML

We especially encourage demos of working AutoML systems; demo proposals are submitted through an accompanying paper. The best 2-3 papers will be invited for oral plenary presentation. All other accepted papers will be presented as posters and short poster spotlight presentations.

For submission details please see

Confirmed Invited speakers:

- Chelsea Finn

- Yolanda Gil

- Luc de Raedt

- Ameet Talwalkar

Chairs: Roman Garnett, Frank Hutter, Joaquin Vanschoren

Organizing committee: Pavel Brazdil, Christophe Giraud-Carrier, Isabelle Guyon

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