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Workshop
Real World Experiment Design and Active Learning
Ilija Bogunovic · Willie Neiswanger · Yisong Yue

Sat Jul 18 07:00 AM -- 03:35 PM (PDT) @
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Event URL: https://realworldml.github.io/ »

This workshop aims to bring together researchers from academia and industry to discuss major challenges, outline recent advances, and highlight future directions pertaining to novel and existing large-scale real-world experiment design and active learning problems. We aim to highlight new and emerging research opportunities for the machine learning community that arise from the evolving needs to make experiment design and active learning procedures that are theoretically and practically relevant for realistic applications.

The intended audience and participants include everyone whose research interests, activities, and applications involve experiment design, active learning, bandit/Bayesian optimization, efficient exploration, and parameter search methods and techniques. We expect the workshop to attract substantial interest from researchers working in both academia and industry. The research of our invited speakers spans both theory and applications, and represents a diverse range of domains where experiment design and active learning are of fundamental importance (including robotics & control, biology, physical sciences, crowdsourcing, citizen science, etc.).


The schedule is with respect to UTC (i.e., Universal Time) time zone.

Keywords: Active Learning · Experiment Design · Real World

Author Information

Ilija Bogunovic (ETH Zurich)
Willie Neiswanger (Carnegie Mellon University)
Yisong Yue (Caltech)
Yisong Yue

Yisong Yue is a Professor of Computing and Mathematical Sciences at Caltech and (via sabbatical) a Principal Scientist at Latitude AI. His research interests span both fundamental and applied pursuits, from novel learning-theoretic frameworks all the way to deep learning deployed in autonomous driving on public roads. His work has been recognized with multiple paper awards and nominations, including in robotics, computer vision, sports analytics, machine learning for health, and information retrieval. At Latitude AI, he is working on machine learning approaches to motion planning for autonomous driving.

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