Weak Supervision

Weak Supervision refers to the process of using less precise, often noisier sources of supervision to train machine learning models. This approach is typically used when there is a lack of sufficient labeled data for training. Weak supervision may involve heuristics or rules to generate labels.

Synonyms:

Weakly Supervised, Weakly Supervised Learning

Papers published in this field over the years:

Hierarchy

Publications for Weak Supervision

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