Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods

Weak supervision is a popular method for building machine learning models without relying on ground truth annotations. Instead, it generates probabilistic training labels by estimating the accuracies of multiple noisy labeling sources (e.g., heuristics, crowd workers)... (read more)

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