Efficient ML Lifecycle Transferring for Large-Scale and High-Dimensional Data via Core Set-Based Dataset Similarity
Developing an end-to-end machine learning (ML) lifecycle for an ML task can be costly and time-consuming. It involves exploring multiple configurations of ML pipelines, encompassing data preparation, ML model design, training, and deployment. While automated ML (AutoML) can assist in automatically s...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10185033/ |