The IEEE Workshop on “Sparse, Uncertain, and Incomplete Data Modeling and Online Learning (DMOL)” will be held on August 10, 2017, in conjunction with the IEEE International Conference on Big Knowledge (ICBK 2017), which takes place between August 9 and August 10 2017 in Hefei, Anhui, China, and which provides a leading international forum for disseminating the latest research in the growing field of “big knowledge”.
The goal of the workshop is to address innovative techniques, metrics, and applications that can exploit data modeling and online learning capabilities to address the Sparse, Uncertain, and Incomplete data challenges facing real-world applications.
Research Topics Covered: Manuscripts are solicited to address a wide range of topics in Sparse, Uncertain, and Incomplete Data Modeling and Online Learning, but not limited to the following:
Data Streaming Mining
Feature Streaming Mining
Sparse Data/Knowledge Representation
Concept Drifting Detection on Big Data
Collaborative Learning on Big Data
Mining from Multiple Data Sources
Uncertain Data Stream Mining
08月10日
2017
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