AI RESEARCH
Learning Over Dirty Data with Minimal Repairs
arXiv CS.LG
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ArXi:2503.13921v2 Announce Type: replace Missing data often exists in real-world datasets, requiring significant time and effort for data repair to learn accurate models. In this paper, we show that imputing all missing values is not always necessary to achieve an accurate ML model. We