Shallow and Deep Non-IID Learning on Complex Data
- Publisher:
- ACM
- Publication Type:
- Conference Proceeding
- Citation:
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2022, pp. 4774-4775
- Issue Date:
- 2022-08-14
Closed Access
Filename | Description | Size | |||
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3534678.3542605.pdf | Published version | 1.35 MB |
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Non-IID (i.i.d.) data holds complex non-IIDness, e.g., couplings and interactions (non-independent) and heterogeneities (not IID drawn from a given distribution). Non-IID learning emerges as a major challenge to shallow and deep learning, including classic statistical learning, mathematical modeling, shallow machine learning, and deep neural learning. Here, we outline the problem, research map, main challenges and topics of shallow and deep non-IID learning.
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