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The KDD 2021 Workshop on Causal Discovery (CD2021)

Published: 14 August 2021 Publication History

Abstract

As a basic and effective tool for explanation, prediction and decision making, causal relationships have been utilized in almost all disciplines. Traditionally, causal relationships are identified by making use of interventions or randomized controlled experiments. However, conducting such experiments is often expensive or even impossible due to cost or ethical concerns. Therefore, there has been an increasing interest in discovering causal relationships based on observational data, and in the past few decades, significant contributions have been made to this field by computer scientists.
Inspired by such achievements and following the success of CD 2016 - CD 2020, CD 2021 continues to serve as a forum for researchers and practitioners in data mining and other disciplines to share their recent research in causal discovery in their respective fields and to explore the possibility of interdisciplinary collaborations in the study of causality. Based on the platform of KDD, this workshop is especially interested in attracting contributions that link data mining/machine learning research with causal discovery, and solutions to causal discovery in large-scale datasets.

Reference

[1]
G. F. Cooper et.al, The Center for causal discovery of biomedical knowledge from Big Data. Journal of the American Medical Informatics Association 1--6, 2015.

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  1. The KDD 2021 Workshop on Causal Discovery (CD2021)

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      cover image ACM Conferences
      KDD '21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
      August 2021
      4259 pages
      ISBN:9781450383325
      DOI:10.1145/3447548
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      New York, NY, United States

      Publication History

      Published: 14 August 2021

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      1. causal discovery
      2. causality
      3. data mining
      4. reasoning

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      KDD '21
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