Learning with Small Data: Subgraph Counting Queries
Abstract Deep Learning (DL) has been widely used in many applications, and its success is achieved with large training data. A key issue is how to provide a DL solution when there is no large training data to learn initially. In this paper, we explore a meta-learning approach for a specific problem,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-09-01
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| Series: | Data Science and Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s41019-023-00223-w |