Self-Supervised Learning

Intermediate

Learning from data by constructing “pseudo-labels” (e.g., next-token prediction, masked modeling) without manual annotation.

Full Definition

Learning from data by constructing “pseudo-labels” (e.g., next-token prediction, masked modeling) without manual annotation.

Keywords

pretraining contrastive masked

Domains

Machine Learning

Related Terms

Machine Learning narrower than

A subfield of AI where models learn patterns from data to make predictions or decisions, improving with experience ra...

 Online Learning related to

Learning where data arrives sequentially and the model updates continuously, often under changing distributions.

 Transfer Learning related to

Reusing knowledge from a source task/domain to improve learning on a target task/domain, typically via pretrained mod...

 Multitask Learning related to

Training one model on multiple tasks simultaneously to improve generalization through shared structure.

 Meta-Learning related to

Methods that learn training procedures or initializations so models can adapt quickly to new tasks with little data.

 Machine Learning related to

A subfield of AI where models learn patterns from data to make predictions or decisions, improving with experience ra...

 Supervised Learning related to

Learning a function from input-output pairs (labeled data), optimizing performance on predicting outputs for unseen i...

 Unsupervised Learning related to

Learning structure from unlabeled data, such as discovering groups, compressing representations, or modeling data dis...

 Semi-Supervised Learning related to

Training with a small labeled dataset plus a larger unlabeled dataset, leveraging assumptions like smoothness/cluster...

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