A Survey of Human-In-The-Loop for Machine Learning

By Xingjiao Wu et al.

Read the original document by opening this link in a new tab.

Table of Contents

1. Introduction
2. Data Processing
3. Model Training
4. Iterative Labeling
5. Challenges
6. Conclusion

Summary

This paper provides a comprehensive survey of human-in-the-loop for machine learning. It discusses the integration of human knowledge into machine learning systems, the challenges faced, and possible solutions. The survey categorizes works based on data processing, model training, and system construction. It emphasizes the importance of incorporating human wisdom to enhance machine learning outcomes. The paper concludes with a list of challenges and opportunities for future research in the field.