Results for "generalization bounds"

Alternative formulation providing bounds.

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

Techniques that discourage overly complex solutions to improve generalization (reduce overfitting).

Number of samples per gradient update; impacts compute efficiency, generalization, and stability.

A high-capacity language model trained on massive corpora, exhibiting broad generalization and emergent behaviors.

Ordering training samples from easier to harder to improve convergence or generalization.

Measures a model’s ability to fit random noise; used to bound generalization error.

A narrow minimum often associated with poorer generalization.

A wide basin often correlated with better generalization.

Built-in assumptions guiding learning efficiency and generalization.

How well a model performs on new data drawn from the same (or similar) distribution as training.