IHML: Incremental Heuristic Meta-Learner
The landscape of machine learning constantly demands innovative approaches to enhance algorithms’ performance across diverse tasks. Meta-learning, known as “learning to learn” is a promising way to overcome these diversity challenges by blending multiple algorithms. This study introduces the IHML: I...
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| Main Authors: | Onur Karadeli, Kıymet Kaya, Şule Gündüz Öğüdücü |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Applied Artificial Intelligence |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08839514.2024.2434309 |
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