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Proceedings of Machine Learning Research | Proceedings of 2018 ACM SIGKDD Workshop on Causal Discovery Held in London, UK on 20 August 2018 Published as Volume 92 by the Proceedings of Machine Learning Research on 09 August 2018. Volume Edited by: Thuc Duy Le Kun Zhang Emre Kıcıman Aapo Hyvärinen Lin Liu Series Editors: Neil D. Lawrence Mark Reid
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Volume 92: Proceedings of 2018 ACM SIGKDD Workshop on Causal Discovery, 20 August 2018, London, UK

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Editors: Thuc Duy Le, Kun Zhang, Emre Kıcıman, Aapo Hyvärinen, Lin Liu

[bib][citeproc]

Preface: The 2018 ACM SIGKDD Workshop on Causal Discovery

Thuc Duy Le, Kun Zhang, Emre Kıcıman, Aapo Hyvärinen, Lin Liu; Proceedings of 2018 ACM SIGKDD Workshop on Causal Disocvery, PMLR 92:1-3

Automated Identification of Causal Moderators in Time-Series Data

Min Zheng, Jan Claassen, Samantha Kleinberg; Proceedings of 2018 ACM SIGKDD Workshop on Causal Disocvery, PMLR 92:4-22

Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding

Daniel Malinsky, Peter Spirtes; Proceedings of 2018 ACM SIGKDD Workshop on Causal Disocvery, PMLR 92:23-47

Evaluation of Causal Structure Learning Methods on Mixed Data Types

Vineet K. Raghu, Allen Poon, Panayiotis V. Benos; Proceedings of 2018 ACM SIGKDD Workshop on Causal Disocvery, PMLR 92:48-65

Causal Relationship Prediction with Continuous Additive Noise Models

Mandar Chaudhary, Nagiza F. Samatova; Proceedings of 2018 ACM SIGKDD Workshop on Causal Disocvery, PMLR 92:66-81

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