Gradient-to-parameter ratio guided feature alignment for model adaptation

A system for adapting artificial intelligence (AI) models to different domains, comprising:

• a memory device;
• one or more processor devices operatively coupled with the memory device to:
• compute activation statistics for an AI model from collected domain data;
• adjust weights of layers of the AI model based on the activation statistics by employing metrics of training gradients;
• fine-tune the AI model by focusing adaptation intensity to layers with attention mechanism by using a ratio of gradient norm over parameter norm to obtain a fine-tuned AI model;
• and
• perform downstream tasks with healthcare images using the fine-tuned AI model.

A non-transitory computer program product comprising a computer-readable storage medium including program code for adapting artificial intelligence (AI) models to different domains, wherein the program code when executed on a computer causes the computer to:

• compute activation statistics for an AI model from collected domain data;
• adjust weights of layers of the AI model based on the activation statistics by employing metrics of training gradients;
• fine-tune the AI model by focusing adaptation intensity to layers with attention mechanism by using a ratio of gradient norm over parameter norm to obtain a fine-tuned AI model;
• and
• perform downstream tasks with healthcare images using the fine-tuned AI model.