*Proceedings Accepted and presented papers will be published into the Conference Proceedings, indexed by Ei compendex, Scopus, etc. *Previous ICCDA Past ICCDA papers were all published in the prestigious ACM proceedings: ICCDA 2021, ISBN: 978-1-4503-8911-2, online: soon ICCDA 2020, ISBN: 978-1-4503-7644-0, EI, Scopus indexed ICCDA 2019, ISBN: 978-1-4503-6634-2, EI, Scopus indexed ICCDA 2018, ISBN: 978-1-4503-6359-4, EI, Scopus indexed ICCDA 2017, ISBN: 978-1-4503-5241-3, EI, Scopus indexed

Call For Papers

*Submission Link


Mathematical, probabilistic and statistical models and theories

Machine learning theories, models and systems

Knowledge discovery theories, models and systems

Manifold and metric learning

Deep learning

Scalable analysis and learning

Non-iidness learning

Heterogeneous data/information integration

Data pre-processing, sampling and reduction

Dimensionality reduction

Feature selection, transformation and construction

Large scale optimization

High performance computing for data analytics

Architecture, management and process for data science

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Ms. Maggie Lau

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Wechat: iconf-cs