Non-transitory computer-readable storage medium, information processing device, and information processing method
AssigneeFujitsu Limited
InventorsSuguru YASUTOMI, Tomohiro HAYASE, Takashi KATOH
Life of this patent
Estimating the term…
Abstract
A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes acquiring a first machine learning model trained by using a training data set including first data and a second machine learning model not trained with the specific data; and retraining the first machine learning model so that an output of the first machine learning model and an output of the second machine learning model when second data corresponding to the first data is input get close to each other.
Claims9
A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process comprising:
- acquiring a first machine learning model trained by using a training data set including first data and a second machine learning model not trained with the first data;
- and
- retraining the first machine learning model so that an output of the first machine learning model and an output of the second machine learning model when second data corresponding to the first data is input get close to each other.
An information processing device comprising:
- one or more memories;
- and
- one or more processors coupled to the one or more memories and the one or more processors configured to
- acquire a first machine learning model trained by using a training data set including first data and a second machine learning model not trained with the first data, and
- retrain the first machine learning model so that an output of the first machine learning model and an output of the second machine learning model when second data corresponding to the first data is input get close to each other.
An information processing method for a computer to execute a process comprising:
- acquiring a first machine learning model trained by using a training data set including first data and a second machine learning model not trained with the specific data;
- and
- retraining the first machine learning model so that an output of the first machine learning model and an output of the second machine learning model when second data corresponding to the first data is input get close to each other.
Dependencies are inferred from the claim text.