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Workshop
8th ICML Workshop on Automated Machine Learning (AutoML 2021)
Gresa Shala · Frank Hutter · Joaquin Vanschoren · Marius Lindauer · Katharina Eggensperger · Colin White · Erin LeDell

Fri Jul 23 06:00 AM -- 01:30 PM (PDT) @
Event URL: https://www.icml2021.automl.org »

Machine learning (ML) 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 robust, off-the-shelf ML 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 ML researchers in different fields of ML connected to AutoML, such as neural architecture search (NAS), hyperparameter optimization, meta-learning, and learning-to-learn, to domain experts aiming to apply ML to new types of problems.

Author Information

Gresa Shala (University of Freiburg)
Frank Hutter (University of Freiburg and Bosch Center for Artificial Intelligence)
Frank Hutter

Frank Hutter is a Full Professor for Machine Learning at the Computer Science Department of the University of Freiburg (Germany), where he has been a faculty member since 2013. Before that, he was at the University of British Columbia (UBC) for eight years, for his PhD and postdoc. Frank's main research interests lie in machine learning, artificial intelligence and automated algorithm design. For his 2009 PhD thesis on algorithm configuration, he received the CAIAC doctoral dissertation award for the best thesis in AI in Canada that year, and with his coauthors, he received several best paper awards and prizes in international competitions on automated machine learning, SAT solving, and AI planning. Since 2016 he holds an ERC Starting Grant for a project on automating deep learning based on Bayesian optimization, Bayesian neural networks, and deep reinforcement learning.

Joaquin Vanschoren (Eindhoven University of Technology)
Marius Lindauer (Leibniz University Hannover)
Katharina Eggensperger (University of Freiburg)
Colin White (Abacus.AI)
Erin LeDell (H2O.AI)

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