TASK-ADAPTIVE ARCHITECTURE FOR FEW-SHOT LEARNING

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...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: KARLINSKY, LEONID, DOVEH, SIVAN, SCHWARTZ, ELIYAHU
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Beschreibung
Zusammenfassung: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).