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Found 2 papers, 1 papers with code
REIN: A Comprehensive Benchmark Framework for Data Cleaning Methods in ML Pipelines
In this work, we introduce a comprehensive benchmark, called REIN1, to thoroughly investigate the impact of data cleaning methods on various ML models.
DiffML: End-to-end Differentiable ML Pipelines
In this paper, we present our vision of differentiable ML pipelines called DiffML to automate the construction of ML pipelines in an end-to-end fashion.
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