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Workshop
7th ICML Workshop on Automated Machine Learning (AutoML 2020)
Frank Hutter · Joaquin Vanschoren · Marius Lindauer · Charles Weill · Katharina Eggensperger · Matthias Feurer · Matthias Feurer

Sat Jul 18 06:00 AM -- 02:55 PM (PDT) @ None
Event URL: http://icml2020.automl.org/ »

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.

The schedule is wrt CEST (i.e., the time zone of Vienna)

Sat 6:00 a.m. - 6:05 a.m. [iCal]
Frank Hutter
Sat 6:05 a.m. - 6:30 a.m. [iCal]

Machine learning models are deployed as part of wider systems where outputs of one model are consumed by other models. This composite structure for machine learning systems is the dominant approach for deploying artificial intelligence. Such deployed systems can be complex to understand, they bring with them intellectual debt. In this talk we'll argue that the next frontier for automated machine learning is to move to automation of the systems design, going from AutoML to AutoAI.

Video

Neil Lawrence
Sat 6:05 a.m. - 6:05 a.m. [iCal]
1min Intro (Intro)
Sat 6:30 a.m. - 6:45 a.m. [iCal]
Keynote Q&A (Q&A)
Sat 6:45 a.m. - 7:00 a.m. [iCal]
Jack Parker-Holder, Vu Nguyen, Stephen Roberts
Sat 7:00 a.m. - 7:10 a.m. [iCal]
Contributed Talk 1 Q&A (Q&A)
Sat 7:10 a.m. - 7:15 a.m. [iCal]
Nic Kuo
Sat 7:10 a.m. - 7:15 a.m. [iCal]
Jonas Mueller
Sat 7:10 a.m. - 7:15 a.m. [iCal]
Eric Lee
Sat 7:10 a.m. - 7:15 a.m. [iCal]
Masahiro Nomura
Sat 7:10 a.m. - 7:15 a.m. [iCal]
Arnout Devos, Matt Grossglauser
Sat 7:15 a.m. - 7:20 a.m. [iCal]
Guillaume Baudart, Peter D. Kirchner, Martin Hirzel, Kiran Kate
Sat 7:15 a.m. - 7:20 a.m. [iCal]
AJ Piergiovanni
Sat 7:15 a.m. - 7:20 a.m. [iCal]
SUILAN Estévez Velarde
Sat 7:15 a.m. - 7:20 a.m. [iCal]
Vu Nguyen
Sat 7:15 a.m. - 7:20 a.m. [iCal]
Diana Cai
Sat 7:20 a.m. - 7:25 a.m. [iCal]
Sauptik Dhar
Sat 7:20 a.m. - 7:25 a.m. [iCal]
Pari Ram, Sijia Liu
Sat 7:20 a.m. - 7:25 a.m. [iCal]
Colin White
Sat 7:20 a.m. - 7:25 a.m. [iCal]
fela Winkelmolen, Nikita Ivkin, H. Furkan Bozkurt, Zohar Karnin
Sat 7:20 a.m. - 7:25 a.m. [iCal]
Afonso José Costa
Sat 7:25 a.m. - 7:30 a.m. [iCal]
, Kuan-Yu Chang, Zhang-Wei Hong, Chun-Yi Lee
Sat 7:25 a.m. - 7:30 a.m. [iCal]
Carlos Medina, Arnout Devos, Matt Grossglauser
Sat 7:25 a.m. - 7:30 a.m. [iCal]
Manas Gupta
Sat 7:25 a.m. - 7:30 a.m. [iCal]
Xavier Fontes
Sat 7:30 a.m. - 8:40 a.m. [iCal]
Poster Session 1 (Poster Session)
Sat 8:40 a.m. - 8:55 a.m. [iCal]
Valerio Perrone
Sat 8:40 a.m. - 8:45 a.m. [iCal]
1 min Intro (Intro)
Sat 8:55 a.m. - 9:10 a.m. [iCal]
Contributed Talk 2 Q&A (Q&A)
Sat 9:10 a.m. - 10:50 a.m. [iCal]
Break
Sat 10:50 a.m. - 11:15 a.m. [iCal]

In this keynote session, I will explain the unique characteristics of healthcare that make it a challenging but extremely promising domain in which to apply AutoML. I will give an overview of several novel approaches we has developed to tackle problems as complex and diverse as AutoML for survival analysis, causal inference, and dynamic forecasting from time-series data. I will also highlight medical AutoML frameworks used in real-world contexts, including predictive tools deployed in response to the COVID-19 pandemic.

Video

Mihaela van der Schaar
Sat 10:50 a.m. - 10:50 a.m. [iCal]
1min Intro (Intro)
Sat 11:15 a.m. - 11:30 a.m. [iCal]
Keynote Talk Q&A (Q&A)
Sat 11:30 a.m. - 11:45 a.m. [iCal]
Zhengying Liu
Sat 11:45 a.m. - 11:55 a.m. [iCal]
Contributed Talk 3 Q&A (Q&A)
Sat 11:55 a.m. - 12:00 p.m. [iCal]
Joeran Beel
Sat 11:55 a.m. - 12:00 p.m. [iCal]
Matthias König
Sat 11:55 a.m. - 12:00 p.m. [iCal]
Colin White
Sat 11:55 a.m. - 12:00 p.m. [iCal]
David Alvarez-Melis
Sat 11:55 a.m. - 12:00 p.m. [iCal]
Martin Binder
Sat 12:00 p.m. - 12:05 p.m. [iCal]
Krsto Proroković
Sat 12:00 p.m. - 12:05 p.m. [iCal]
Misha Khodak
Sat 12:00 p.m. - 12:05 p.m. [iCal]
Yufei Wang, Tianwei Ni
Sat 12:00 p.m. - 12:05 p.m. [iCal]
Joeran Beel
Sat 12:00 p.m. - 12:05 p.m. [iCal]
Syrine Belakaria
Sat 12:05 p.m. - 12:10 p.m. [iCal]
Sulin Liu
Sat 12:05 p.m. - 12:10 p.m. [iCal]
Pedro F da Costa
Sat 12:05 p.m. - 12:10 p.m. [iCal]
Sujen Shah, Mitar Milutinovic
Sat 12:05 p.m. - 12:10 p.m. [iCal]
Erin LeDell
Sat 12:05 p.m. - 12:10 p.m. [iCal]
Samuel Glass
Sat 12:15 p.m. - 1:15 p.m. [iCal]
Poster Session 2 (Poster Session)
Sat 1:15 p.m. - 1:40 p.m. [iCal]
Alex Smola
Sat 1:40 p.m. - 1:55 p.m. [iCal]
Keynote Talk Q&A (Q&A)
Sat 1:55 p.m. - 2:00 p.m. [iCal]
Short Break (Break)
Sat 2:00 p.m. - 2:55 p.m. [iCal]
Panel Discussion
Neil Lawrence, Mihaela van der Schaar, Alex Smola, Valerio Perrone, Jack Parker-Holder, Zhengying Liu

Author Information

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 (TU Eindhoven / OpenML)

Joaquin Vanschoren is an assistant professor at the Eindhoven University of Technology. His research focuses on automated machine learning and meta-learning. He has received the Dutch Data prize in 2016 and an Amazon Research Award in 2019. He is a regular invited speaker at international conferences and workshops (including NeurIPS, ICML, the UN summit on AI for Good, and the Dutch eScience Symposium), and regularly gives talks at companies (e.g. Amazon Cambridge, Amazon Berlin, IBM New York). He also gives regular tutorials on meta-learning (including at NeurIPS 2018 and the ACDL summer school). He is co-editor and co-author of the reference book on Automated Machine Learning. He co-organizes the Automated Machine Learning workshop series at ICML and the meta-learning workshop series at NeurIPS. He was also general chair, program chair, and/or demo chair at European machine learning conferences. He also founded and runs OpenML.org, a popular open science platform for machine learning, with over 150.000 yearly users worldwide. His work has been mentioned in Science Magazine, ACM Explorations, KDnuggets, and Open Science Radio.

Marius Lindauer (Leibniz University Hannover)
Charles Weill (Google Research)
Katharina Eggensperger (University of Freiburg)
Matthias Feurer (University of Freiburg)
Matthias Feurer (University of Freiburg)

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