Please help forward to interested parties Call For Papers: RobustML Workshop<https://sites.google.com/connect.hku.hk/robustML-2021/home?authuser=0> at ICLR 2021
We invite submissions for the Robust and Reliable Machine Learning in the Real World Workshop (RobustML), which is co-located with ICLR 2021. Both the RobustML workshop and the ICLR 2021 conference will be held in a virtual (online) format. Authors are invited to submit short papers studying aspects of robust and reliable machine learning, and we especially solicit work which aims to bridge the gap to real-world scenarios, such as any of the following topics: * Characterizations of realistic perturbations of datapoints * Real-world distributional shifts * Confidence and uncertainty estimation * Datasets and simulation data for robustness * Real-world specifications and verification * Legal consequences of (un)robust systems * Fairness of robust systems * Robustness in safety-critical applications Please see the workshop website<https://sites.google.com/connect.hku.hk/robustML-2021/home?authuser=0> for the full call for papers, and direct any questions to [email protected]<mailto:[email protected]>. Welcome to join our Slack channel for discussions and questions: https://join.slack.com/t/robustnessworkshop/shared_invite/zt-mllcp0dg-dKnoTJTCp5CClEcysDKf6g . === Important Dates === * Submissions due – Feb. 26, 2021 (11:59 pm AoE) * Notification of Acceptance – Mar 26, 2021 (11:59 pm AoE) * Camera Ready Due – April 15, 2021 (11:59 pm AoE) * Workshop Date – May 8, 2021 === Submission Policy === Submission is via CMT<https://cmt3.research.microsoft.com/RMLICLR2021/Submission/Index> and will undergo a light peer review process. Submissions are limited to four content pages (including all figures and tables), plus unlimited pages for references. Work may be previously published, completed, or ongoing. The workshop will not publish proceedings but all accepted papers will be posted on our workshop website. Accepted papers are also allowed to be submitted to other venues later. === Confirmed Speakers === · Bo Li<https://aisecure.github.io/> - Assistant Professor, UIUC · Dawn Song<https://people.eecs.berkeley.edu/~dawnsong/> - Professor, UC Berkeley · Ece Kamar<https://www.ecekamar.com/> - Senior Principal Research Area Manager, Microsoft Research · Finale Doshi-Velez<https://finale.seas.harvard.edu/> - Associate Professor, Harvard University · Kendra Albert<https://kendraalbert.com/> - Technology Lawyer & Clinical Instructor, Harvard University · Nicolas Papernot<https://www.papernot.fr/> - Assistant Professor, University of Toronto · Percy Liang<https://cs.stanford.edu/~pliang/> - Associate Professor, Stanford University Best, Di Jin (Amazon) Eric Wong (MIT) Yixin Nie (UNC Chapel Hill) Tristan Naumann (Microsoft) Mohit Bansal (UNC Chapel Hill) Yonatan Belinkov (Technion) Kai-Wei Chang (UCLA) Yanjun Qi (University of Virginia) Zhijing Jin (Max Plank Institute) Aditi Raghunathan (Stanford)
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