Model ensemble generation
AssigneeFujitsu Limited
InventorsMasaya KIBUNE, Xuan TAN
Life of this patent
Estimating the term…
Abstract
A method of generating a model ensemble may be provided. A method may include training a base model including a plurality of layers. The method may also include generating a plurality of models for the neural network based on the base model. Each model of the plurality of models includes a plurality of layers. Further, the method may include modifying a layer of each of the plurality of models such that each model of the plurality of models includes a layer modified with respect to an associated layer of each of the base model and each of the other plurality of models. In addition, the method may include tuning each modified layer of the plurality of models.
Claims20
A method of generating a model ensemble, comprising:
- training, via at least one processor, a base model including a plurality of layers;
- generating, via the at least one processor, a plurality of models for the model ensemble based on the base model, each model of the plurality of models including a plurality of layers;
- modifying, via the at least one processor, a layer of each of the plurality of models such that each model of the plurality of models includes a layer modified with respect to an associated layer of each of the base model and an associated layer of each of the other plurality of models;
- and
- tuning, via the at least one processor, each modified layer of the plurality of models.
One or more non-transitory computer-readable media that include instructions that, when executed by one or more processors, are configured to cause the one or more processors to perform operations, the operations comprising:
- training a base model including a plurality of layers;
- generating a plurality of models for a model ensemble based on the base model, each model of the plurality of models including a plurality of layers;
- modifying a layer of each of the plurality of models such that each model of the plurality of models includes a layer modified with respect to an associated layer of each of the base model and an associated layer of each of the other plurality of models;
- and
- tuning each modified layer of the plurality of models.
Dependencies are inferred from the claim text.