[Apologies if you receive multiple copies of this message] ICML 2020 Workshop: Human Interpretability in Machine Learning
July 17, 2020 Virtual event (starting at 10am CEST) https://sites.google.com/view/whi2020 The Fifth Annual Workshop on Human Interpretability in Machine Learning (WHI 2020), held in conjunction with ICML 2020<https://icml.cc/Conferences/2020/>, will bring together artificial intelligence (AI) researchers who study the interpretability of AI systems, develop interpretable machine learning algorithms, and develop methodologies to interpret black-box machine learning models (e.g., post-hoc interpretations). This year we will have a special focus on Interpretability in Practice, encouraging submissions discussing practical applications of interpretability algorithms, requirements, and tools for specific stakeholders (e.g., lawyers, policymakers, finance experts, medical professionals). Participants in the workshop will exchange ideas on these and allied topics, including: * Quantifying and axiomatizing interpretability * Psychology of human concept learning * Rule learning, symbolic regression, and case-based reasoning * Generalized additive models, sparsity, and interpretability * Interpretation of black-box models (including deep neural networks) * Interpretable unsupervised models (clustering, topic models, etc.) * Causality analysis of predictive models * Verifying, diagnosing, and debugging machine learning systems * Interpretability in reinforcement learning * Visual analytics of model innards * Real-world experiences of deploying interpretability at scale * Transparent models for auditability * Interdisciplinary work regarding transparency at scale Call for Papers and Submission Instructions We invite submissions of full papers as well as works-in-progress, position papers, and papers describing open problems and challenges. While original contributions are preferred, we also invite submissions of high-quality work that has recently been published in other venues or is concurrently submitted. Papers should be 4-6 pages in length (excluding references and acknowledgments) formatted using the ICML template<https://media.icml.cc/Conferences/ICML2020/Styles/icml2020_style.zip> (in the blind non-accepted mode) and submitted online at https://cmt3.research.microsoft.com/WHI2020. We expect submissions to be 4 pages but will allow up to 6 pages. Accepted papers will be selected for a short oral presentation. Non-archival proceedings will be created as an overlay on arXiv. Key Dates Submission deadline: June 22, 2020 Notification: July 8, 2020 Workshop: July 17, 2020 Invited Talks Finale Doshi-Velez<https://finale.seas.harvard.edu>, Paulson School of Engineering and Applied Sciences, Harvard University Mason Kortz<https://cyber.harvard.edu/people/mkortz>, Berkman Klein Center for Internet & Society, Harvard Law School Donald B. Rubin<https://statistics.fas.harvard.edu/people/donald-b-rubin>, Department of Statistics, Tsinghua University Sandra Wachter<https://www.oii.ox.ac.uk/people/sandra-wachter/>, Oxford Internet Institute, University of Oxford Li Xuchun<https://www.linkedin.com/in/lixuchun/?originalSubdomain=sg>, AI Development Office, Monetary Authority of Singapore Organizers Umang Bhatt<https://umangsbhatt.github.io>, University of Cambridge Amit Dhurandhar<http://researcher.watson.ibm.com/researcher/view.php?person=us-adhuran>, IBM Research AI Been Kim<http://beenkim.github.io>, Google Brain Kush R. Varshney<http://krvarshney.github.io>, IBM Research AI Dennis Wei<https://sites.google.com/site/dennislwei>, IBM Research AI Adrian Weller<http://mlg.eng.cam.ac.uk/adrian>, University of Cambridge Alice Xiang<https://www.partnershiponai.org/team/alice-xiang/>, Partnership on AI
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