Abstract: Disclosed herein are an apparatus and method for task-adaptive neural network retrieval based on meta-contrastive learning. The apparatus for task-adaptive neural network retrieval based on meta-contrastive learning includes: memory configured to store a database including a learning model pool consisting of a plurality of datasets and neural networks pre-trained on the datasets and also store a program for task-adaptive neural network retrieval based on meta-contrastive learning; and a controller configured to perform task-adaptive neural network retrieval based on meta-contrastive learning by executing the program. In this case, the controller learns a cross-modal latent space for datasets and neural networks trained on the datasets by calculating the similarity between each dataset and a neural network trained on the dataset while considering constraints included in any one task previously selected from the database, thereby retrieving an optimal neural network.
Type:
Application
Filed:
April 28, 2022
Publication date:
November 17, 2022
Applicants:
AITRICS CO., LTD., KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
Inventors:
Sung Ju HWANG, Wonyong JEONG, Ha Yeon LEE, Geon PARK, Eun Young HYUNG