Machine Learning

The field of building systems that perform tasks associated with human intelligence—perception, reasoning, language...

A branch of ML using multi-layer neural networks to learn hierarchical representations, often excelling in vision, sp...

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

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

A learning paradigm where an agent interacts with an environment and learns to choose actions to maximize cumulative ...

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 ...

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

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

Models that learn to generate samples resembling training data.

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

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