TASK-ADAPTIVE ARCHITECTURE FOR FEW-SHOT LEARNING
Meta-training an artificial neural cell for use in a few-shot learner, wherein the meta-training includes: executing a Neural Architecture Search (NAS) to automatically learn an architecture of the artificial neural cell; training adaptive controllers that are comprised in the architecture of the ar...
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| creator | KARLINSKY, LEONID DOVEH, SIVAN SCHWARTZ, ELIYAHU |
| description | Meta-training an artificial neural cell for use in a few-shot learner, wherein the meta-training includes: executing a Neural Architecture Search (NAS) to automatically learn an architecture of the artificial neural cell; training adaptive controllers that are comprised in the architecture of the artificial neural cell, wherein each of the adaptive controllers is configured to adapt the architecture of the artificial neural cell to a few-shot learning task; and regressing the architecture of the artificial neural cell from support data of the few-shot learning task, through the adaptive controllers. Generating the few-shot learner based on the meta-trained artificial neural cell, to form an Artificial Neural Network (ANN). |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS |
| title | TASK-ADAPTIVE ARCHITECTURE FOR FEW-SHOT LEARNING |
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