Class Imbalance

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

A structured collection of examples used to train/evaluate models; quality, bias, and coverage often dominate outcomes.

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

A continuous vector encoding of an item (word, image, user) such that semantic similarity corresponds to geometric cl...