116 citations · 602 across the 32 of their papers we have counts for
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cs.DB2019
CleanML: A Study for Evaluating the Impact of Data Cleaning on ML Classification Tasks
Peng Li, Xi Rao, Jennifer Blase +3
Data quality affects machine learning (ML) model performances, and data scientists spend considerable amount of time on data cleaning before model training. However, to date, there…
cs.DB2017★ 17 cited
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads
Tian Li, Jie Zhong, Ji Liu +2
We present ease.ml, a declarative machine learning service platform we built to support more than ten research groups outside the computer science departments at ETH Zurich for the…
cs.DB2015★ 14 cited
Incremental Knowledge Base Construction Using DeepDive
Jaeho Shin, Sen Wu, Feiran Wang +3
Populating a database with unstructured information is a long-standing problem in industry and research that encompasses problems of extraction, cleaning, and integration. Recent n…