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Keynote in SKG2017 (August 14-15, 2017, Beijing, China)
Publisher:Manager Updated:2017/6/25

SKG2017 Keynotes.pdf


The 13th International Conference on Semantics, Knowledge and Grids on Big Data, August 14-15, 2017, Beijing, China


Talk Title: Learning from big data with uncertainty.

Abstract: Big data refers to the data-sets that are so large that conventional database management and data analysis tools are insufficient to work with them. Big data has become a bigger-than-ever problem with the quick developments of data collection and storage technologies. Model simplification is one of the most popular approaches to big data processing. After a brief tutorial of the existing techniques of processing big data, this talk will present some key issues of learning from big data with uncertainty, focusing on the impact of handling uncertainty on the model simplification. It shows that the representation, measure, and handling of the uncertainty have a significant influence on the performance of learning from big data. Some new advances in our Big Data Institute regarding the research on big data analysis and its applications to different domains are briefly introduced.

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