2nd International Workshop on Data Quality Assessment for Machine Learning

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Abstract

The 2nd International Workshop on Data Quality Assessment for Machine Learning (DQAML'21) is organized in conjunction with the Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD). This workshop aims to serve as a forum for the presentation of research related to data quality assessment and remediation in AI/ML pipeline. Data quality is a critical issue in the data preparation phase and involves numerous challenging problems related to detection, remediation, visualization and evaluation of data issues. The workshop aims to provide a platform to researchers and practitioners to discuss such challenges across different modalities of data like structured, time series, text and graphical. The aim is to attract perspectives from both industrial and academic circles.

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Patel, H., Ishikawa, F., Berti-Equille, L., Gupta, N., Mehta, S., Masuda, S., … Nishi, Y. (2021). 2nd International Workshop on Data Quality Assessment for Machine Learning. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 4147–4148). Association for Computing Machinery. https://doi.org/10.1145/3447548.3469468

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