Unsupervised Learning

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

Automatically learning useful internal features (latent variables) that capture salient structure for downstream tasks.

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

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

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

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

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

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