Dear all,
We would like to invite you to submit your work to the Workshop on Adaptive Experimental Design and Active Learning in the Real World at ICML 2022, which will be held on July 22/23, 2022 in Baltimore US. *Important Information* ------------------------------- * Website: realworldml.github.io<https://realworldml.github.io/> * Workshop date: July 22 or 23, 2022 * Location: Hybrid (Baltimore, Maryland USA, and Remote) * Submission deadline: 3rd June 2022, 11:59 PM (AoE time) * Contact: realml.icml2...@gmail.com<mailto:realml.icml2...@gmail.com> *Keynote Speakers* --------------------------- * Caroline Uhler (MIT) * Jeff Schneider (CMU) * Ava Soleimany (Microsoft Research) * Kevin Jamieson (University of Washington) * Ruth Misener (Imperial College London) * Peter Frazier (Cornell) * Christopher Langmead (Amgen Inc.) *Call for Papers* ---------------------- 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 experimental design and active learning problems. We aim to highlight new and emerging research opportunities for the ML community that arise from the evolving needs to make experimental design and active learning procedures that are theoretically and practically relevant for realistic applications. Progress in this area has the potential to provide immense benefits in using experimental design and active learning algorithms in emerging high impact applications, such as materials design, computational biology, algorithm configuration, AutoML, crowdsourcing, citizen science, robotics, and more. We welcome submissions of 4-6 pages in JMLR Workshop and Proceedings format<https://www.overleaf.com/latex/templates/template-for-journal-of-machine-learning-research-jmlr-with-jmlr2e-dot-sty/vjcpxhvztrjn> (excluding references). All accepted papers will be presented as posters (recently published or under-review work is also welcome). There will be no archival proceedings, however, the accepted papers will be made available online on the workshop website. Papers should be submitted via Openrevie<https://openreview.net/group?id=ICML.cc/2022/Workshop/ReALML>w. *Topics of Interest* ------------------------- Technical topics of interest include (but are not limited to): * Large-scale and real-world experimental design (e.g. drug design, physics, robotics, material design, protein design, causal discovery). * Efficient active learning and exploration. * Experimental design and active learning in reinforcement learning. * High-dimensional, scalable Bayesian and bandit optimization (e.g. contextual, multi-task, multi-objective). * Sample-efficient interactive learning, hypothesis and A/B testing. * Corrupted or indirect measurements, multi-fidelity experimentation. * Domain-knowledge integration (e.g. from physics, chemistry, biology, etc.). * Safety and robustness during experimentation and of resulting designs. *Organization* ------------------- * Ilija Bogunovic (UCL London) * Mojmír Mutný (ETH Zurich) * Willie Neiswanger (Stanford) * Yisong Yue (Caltech) * Stefano Ermon (Stanford) * Andreas Krause (ETH Zurich) On behalf of the organizing committee, Mojmir Mutny
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