US Patent Application 18312584. METHODS, APPARATUS, AND ARTICLES OF MANUFACTURE TO RE-PARAMETERIZE MULTIPLE HEAD NETWORKS OF AN ARTIFICIAL INTELLIGENCE MODEL simplified abstract
METHODS, APPARATUS, AND ARTICLES OF MANUFACTURE TO RE-PARAMETERIZE MULTIPLE HEAD NETWORKS OF AN ARTIFICIAL INTELLIGENCE MODEL
Organization Name
Inventor(s)
Vinnam Kim of Pyeongtaek-si (KR)
METHODS, APPARATUS, AND ARTICLES OF MANUFACTURE TO RE-PARAMETERIZE MULTIPLE HEAD NETWORKS OF AN ARTIFICIAL INTELLIGENCE MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18312584 titled 'METHODS, APPARATUS, AND ARTICLES OF MANUFACTURE TO RE-PARAMETERIZE MULTIPLE HEAD NETWORKS OF AN ARTIFICIAL INTELLIGENCE MODEL
Simplified Explanation
The patent application describes a method and apparatus for re-parameterizing multiple head networks of an artificial intelligence (AI) model.
- The invention involves training an AI model using both labeled data and pseudo-labeled data.
- The AI model includes multiple head networks.
- After the AI model has been trained, the invention re-parameterizes only the multiple head networks into a fully connected layer.
- Other portions of the AI model are not re-parameterized.
- This re-parameterization process helps optimize the performance of the AI model.
- The invention provides a more efficient and effective way to re-parameterize multiple head networks in an AI model.
Original Abstract Submitted
Systems, apparatus, articles of manufacture, and methods are disclosed re-parameterize multiple head networks of an artificial intelligence model. An example apparatus is to train an AI model using labeled data and pseudo-labeled data, the AI model including multiple head networks. Additionally, the example apparatus is to, after the AI model has been trained, re-parameterize the multiple head networks of the AI model into a fully connected layer without re-parameterizing other portions of the AI model.