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Weak supervision

Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to the large amount of data required to train them. It is characterized by using a combination of a small amount of human-labeled data (exclusively used in more expensive…

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In human cognition

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Weak supervision

Nodes50
Edges49
Triples11
Avg. degree1.96
Density0.04
Components1

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Weak supervision

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related to Weak Supervision in Predictive Maintenance · 4
Weak supervision → By, This, Traditional, Weak

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learning data unlabeled semi-supervised labeled displaystyle supervised manifold models may problems regularization also examples using human transductive algorithms used large

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
images of dogsinstance ofHuman infants are sensitive to the structure of unlabeled natural categories0.80text
cats or maleinstance ofHuman infants are sensitive to the structure of unlabeled natural categories0.80text
female facesinstance ofHuman infants are sensitive to the structure of unlabeled natural categories0.80text
data programminginstance ofBy incorporating techniques0.80text
label modelinginstance ofBy incorporating techniques0.80text
and semi-supervised learninginstance ofBy incorporating techniques0.80text
weak supervision enables the development of robust predictive maintenance systems capable of identifying equipment failures or anomalies with reduced reliance on high-quality labeled datainstance ofBy incorporating techniques0.80text
Weak supervisionrelated to Weak Supervision in Predictive MaintenanceWeak0.60section
Weak supervisionrelated to Weak Supervision in Predictive MaintenanceTraditional0.60section
Weak supervisionrelated to Weak Supervision in Predictive MaintenanceBy0.60section
Weak supervisionrelated to Weak Supervision in Predictive MaintenanceThis0.60section

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