Hi all, We’d like to invite you to submit to the NeurIPS 2022 Workshop on Distribution Shifts. Our focus is on bringing together applications and methods research to facilitate discussion on real-world distribution shifts.
Website: https://sites.google.com/view/distshift2022 Paper submission deadline: October 3, 2022 (Anywhere on Earth) Author notification: October 20, 2022 Workshop: December 3, 2022, in-person in New Orleans, USA. Authors who will not be able to attend in person are still encouraged to submit. Accepted papers will be accompanied by a short pre-recorded video to allow authors to present their work remotely. Please reach out to distshift-workshop-2...@googlegroups.com if you have any questions. Call for papers Distribution shifts—where a model is deployed on a data distribution different from what it was trained on—pose significant robustness challenges in real-world ML applications. Such shifts are often unavoidable in the wild and have been shown to substantially degrade model performance. For example, models can systematically fail when tested on patients from different hospitals; molecules with different scaffolds; images from different cameras; or people from different demographics. Through the workshop, we hope to support and accelerate research on real-world distribution shifts. We are broadly interested in methods, evaluations and benchmarks, and theory for distribution shifts, and we are especially interested in work on distribution shifts that arise naturally in real-world application contexts. Examples of relevant topics include, but are not limited to: - Examples of real-world distribution shifts in various application areas. - Methods for improving robustness to distribution shifts. - Empirical and theoretical characterization of distribution shifts. - Benchmarks and evaluation protocols for distribution shifts. Invited Speakers Alicia Wassink, University of Washington Erin Hartman, UC Berkeley Markus Reichstein, Max Planck Institute for Biogeochemistry Mingsheng Long, Tsinghua University Pradeep Ravikumar, Carnegie Mellon University Sara Beery, Google & MIT Organizers Becca Roelofs, Google Chelsea Finn, Stanford University Fanny Yang, ETH Zurich Hongseok Namkoong, Columbia University Masashi Sugiyama, RIKEN & University of Tokyo Jacob Eisenstein, Google Jonas Peters, University of Copenhagen Pang Wei Koh, University of Washington & Google Shiori Sagawa, Stanford University Yoonho Lee, Stanford University
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