Articles
Multi-task Learning for Joint Prediction: Examining multi-task learning approaches to enable machine learning models to simultaneously perform multiple predictions
Published 07-12-2022
Keywords
- Multi-task learning,
- Joint prediction,
- Machine learning,
- Model training,
- Domain adaptation
- Transfer learning,
- Neural networks,
- Optimization ...More
How to Cite
[1]
Dr. Ahmed Khan, “Multi-task Learning for Joint Prediction: Examining multi-task learning approaches to enable machine learning models to simultaneously perform multiple predictions”, Hong Kong J. of AI and Med., vol. 2, no. 2, pp. 1–11, Dec. 2022, Accessed: Jan. 18, 2025. [Online]. Available: https://hongkongscipub.com/index.php/hkjaim/article/view/12
Abstract
Multi-task learning (MTL) has emerged as a powerful approach in machine learning, enabling models to jointly learn multiple related tasks. This paper provides an overview of MTL for joint prediction, where a single model is trained to make multiple predictions simultaneously. We discuss the motivation behind MTL, its advantages, challenges, and various approaches. We also present a comparative analysis of different MTL techniques, highlighting their strengths and limitations. Additionally, we discuss applications of MTL in various domains and provide insights into future research directions.
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