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US 2026/0119989 A1Published application
Continual learning system and continual learning method
AssigneeDenso Corporation
InventorTARO MURAYAMA
Life of this patent
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Abstract
A continual learning system learns a prediction model that performs prediction on input data, acquires additional data, learns the prediction model, calculates information on past data to be used in a next learning stage, and stores the learned prediction model and the calculated information on the past data. The continual learning system calculates the prediction model and the information of the past data, and calculates statistics of the past data. The statistics provides a learning result equivalent to a learning result obtained when the acquisition unit uses the past data acquired as the additional data in past by the acquisition unit.
Claims12
A continual learning system that learns a prediction model that performs prediction on input data, the continual learning system comprising:
- an acquisition unit configured to acquire additional data;
- a learning unit configured to learn the prediction model based on the additional data, information on past data used for a previous learning stage, and the prediction model learned in the previous learning stage;
- a compression unit configured to calculate the information on the past data to be used in a next learning stage by the learning unit based on the additional data, the information on the past data, and the prediction model learned in the previous learning stage by the learning unit;
- and
- a storage that stores the prediction model learned by the learning unit and the information on the past data calculated by the compression unit,
- wherein
- the learning unit and the compression unit are configured to calculate the prediction model and the information of the past data based on
- the additional data,
- the prediction model stored in the storage, and
- the information on the past data stored in the storage,
- when, in the next learning stage, the learning unit further learns, as the information on the past data, the additional data for the next learning stage, the compression unit calculates statistics of the past data, and
- the statistics provides a learning result equivalent to a learning result obtained when the acquisition unit uses the past data acquired as the additional data in past by the acquisition unit.
9 more elements
A continual learning method comprising:
- learning a prediction model that performs prediction on input data;
- acquiring additional data;
- learning the prediction model based on the additional data, information on past data used for a previous learning stage, and the prediction model learned in the previous learning stage;
- calculating the information on the past data to be used in a next learning stage based on the additional data, the information on the past data, and the prediction model learned in the previous learning stage;
- storing the learned prediction model and the calculated information on the past data;
- calculating the prediction model and the information of the past data based on
- the additional data,
- the stored prediction model, and
- the stored information on the past data;
- and
- when, in the next learning stage, further learning, as the information on the past data, the additional data for the next learning stage, calculating statistics of the past data,
- wherein
- the statistics provides a learning result equivalent to a learning result obtained in a case of using the past data acquired in past as the additional data.
10 more elements
A continual learning system comprising:
- a storage;
- and
- at least one processor with a memory storing computer program code, wherein
- the at least one processor with the memory is configured to cause the continual learning system to:
- learn a prediction model that performs prediction on input data;
- acquire additional data;
- learn the prediction model based on the additional data, information on past data used for a previous learning stage, and the prediction model learned in the previous learning stage;
- and
- calculate the information on the past data to be used in a next learning stage based on the additional data, the information on the past data, and the prediction model learned in the previous learning stage,
- wherein
- the storage stores the learned prediction model and the calculated information on the past data,
- the at least one processor with the memory is further configured to cause the continual learning system to:
- calculate the prediction model and the information of the past data based on
- the additional data,
- the prediction model stored in the storage, and
- the information on the past data stored in the storage;
- and
- when, in the next learning stage, further learning, as the information on the past data, the additional data for the next learning stage, calculate statistics of the past data, and
- the statistics provides a learning result equivalent to a learning result obtained in a case of using the past data acquired in past as the additional data.
16 more elements
Dependencies are inferred from the claim text.