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UAI Causality Workshop 2014 : UAI 2014 Workshop Causal Learning: Inference and Prediction | |||||||||||||
Link: http://staff.science.uva.nl/~jmooij1/uai2014-causality-workshop/index.html | |||||||||||||
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Call For Papers | |||||||||||||
2nd Call for Papers
Workshop "Causal Inference: Learning and Prediction" Uncertainty in Artificial Intelligence 2014 (UAI 2014) Sunday, July 27, 2014 Quebec City, Quebec, Canada Causality is central to how we view and react to the world around us, to our decision making, and to the advancement of science. Causal inference in statistics and machine learning has advanced rapidly in the last 20 years, leading to a plethora of new methods, both for causal structure learning and for making causal predictions (i.e., predicting what happens under interventions). However, a side-effect of the increased sophistication of these approaches is that they have grown apart, rather than together. The aim of this workshop is to bring together researchers interested in the challenges of causal inference from observational and interventional data, especially when latent (confounding) variables or feedback loops may be present. Contributions describing practical applications of causal methods are specially encouraged. This one-day workshop will explore these topics through a set of invited talks, presentations and a poster session. We encourage co-submission of (full) papers that have been submitted to the main UAI 2014 conference. See our website for updates: http://staff.science.uva.nl/~jmooij1/uai2014-causality-workshop/ [This workshop takes place directly after the 30th Conference on Uncertainty in Artificial Intelligence (UAI), 23-26 July, 2014.] Example Topics: ============== * Addressing the challenge of practical causal inference in the context of real applications; * Developing measures and methods for evaluating the quality of causal predictions; * Feasible prediction of post-interventional distributions by reconstructing latent confounders; * Considering the relative robustness of assumptions and algorithms to model misspecification; * Methods for causal inference from high-dimensional data; * Methods for combining different datasets; * Experimental design for causal inference; * Real-world validation of causal inference methods; * Discussions on the possibility of making causal predictions in a highly confounded and cyclic world; * Occam’s Razor in causal inference (methodological justifications for oversimplified models). Submission ========= There are two possible submission formats. The authors can either submit: - a one-page abstract (including references) describing recently published work, or - a full-length paper, limited to 9 pages (including figures and text, excluding references). If a contribution consists of material that has been published elsewhere earlier on (except possibly at UAI 2014), the authors must choose the one-page abstract format and cite the original work. Our submission deadline comes a few days after the UAI author notification deadline. We encourage co-submission of (full) papers that have been submitted to the main UAI 2014 conference. Please indicate if your paper was also submitted to UAI. If accepted for UAI, the paper would be published in UAI proceedings, but we may also invite the authors to give a (oral or poster) presentation at the workshop. Style files for full papers can be found on the UAI website: http://auai.org/uai2014/ Abstracts and papers must be submitted via e-mail before the deadline (June 6) to: uai2014.causality.workshop@gmail.com Contributions will be peer reviewed by at least two reviewers. Accepted papers will be presented either as oral presentation or in a poster session. Proceedings ========== After the workshop we will publish proceedings on CEUR-WS and via the web-page: http://staff.science.uva.nl/~jmooij1/uai2014-causality-workshop/ Authors of accepted papers can choose to contribute the submitted manuscript (i.e., the full paper or the abstract). They can also choose not to contribute to the proceedings. Oral presentation slides will also be disseminated via the workshop web-page. Important Dates ============== * June 6 2014: Submission deadline for abstracts and full papers * June 27 2014: Author notification * July 27 2014: Workshop (following the UAI 2014 main conference, July 24-26) Organizers ========= Joris Mooij (Chair), University of Amsterdam Dominik Janzing, Max Planck Institute of Intelligent Systems Jonas Peters, ETH Zürich Tom Claassen, Radboud University Nijmegen Antti Hyttinen, California Institute of Technology |
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