Patel H., Ishikawa F., Berti-Equille Laure, Gupta N., Mehta S., Masuda S., Mujumdar S., Afzal S., Bedathur S., Nishi Y. (2021). 2nd international workshop on data quality assessment for machine learning [résumé]. In :
KDD'21 : proceedings of the 27th ACM SIGKDD conference on knowledge discovery and data mining. New York : ACM, 4147-4148. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 27., [En ligne] Singapour (SGP), 2021/08/14-18. ISBN 978-1-4503-8332-5.
Titre du document
2nd international workshop on data quality assessment for machine learning [résumé]
Année de publication
2021
Auteurs
Patel H., Ishikawa F., Berti-Equille Laure, Gupta N., Mehta S., Masuda S., Mujumdar S., Afzal S., Bedathur S., Nishi Y.
In
KDD'21 : proceedings of the 27th ACM SIGKDD conference on knowledge discovery and data mining
Source
New York : ACM, 2021,
4147-4148 ISBN 978-1-4503-8332-5
Colloque
ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 27., [En ligne] Singapour (SGP), 2021/08/14-18
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 platformto 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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
;
Informatique [122]
Localisation
Fonds IRD [F B010085547]
Identifiant IRD
fdi:010085547
