We invite researchers to submit their recent work that studies how ML techniques can be used to facilitate and automate a range of data operations (e.g. ML-assisted labeling, synthesis, selection, augmentation), and the associated challenges of quality, security, privacy and fairness for which ML techniques can also enable solutions. Topics of interest include but are not limited to:
- Methods of using ML to assist human annotators in data labeling
- Methods of automated data engineering, such as synthesis, augmentation, re-weighting, etc.
- Theories, methods, and studies to characterize, detect, or mitigate data bias
- Methods of detecting and preserving privacy information in data
- Systems for automating data operations and analytics
- Applications based on data-human-machine interactions
Authors are welcome to submit 4-6 page papers, with unlimited space for references and appendices (all submitted as a single PDF file). The submissions should follow the ICML 2021 style and formatting guidelines. The review process is double-blind. The submissions should not have been previously published nor have appeared in the ICML main conference. Work currently under submission to another conference is welcome.
Paper submission deadline: June 14, 2021 (11:59pm AOE)
Papers can be submitted at the following link: https://cmt3.research.microsoft.com/ICML2021ML4data
Submissions will be accepted as contributed talks or poster presentations. Accepted papers will be posted on the workshop website. Accepted papers are free to appear in other journals or conference proceedings.