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Found 3 papers, 2 papers with code
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report)
First, to reduce the cost of human annotators, we use Infl, which prioritizes the most influential training samples for cleaning and provides cleaned labels to save the cost of one human annotator.
DeltaGrad: Rapid retraining of machine learning models
Machine learning models are not static and may need to be retrained on slightly changed datasets, for instance, with the addition or deletion of a set of data points.
PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models
The ubiquitous use of machine learning algorithms brings new challenges to traditional database problems such as incremental view update.
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