Results for "domain adaptation"

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

Randomly zeroing activations during training to reduce co-adaptation and overfitting.

A mismatch between training and deployment data distributions that can degrade model performance.

Randomizing simulation parameters to improve real-world transfer.