Robustness in Machine Learning: A Systematic Review

This comprehensive review discusses various methods to enhance the robustness of machine learning models, examining the trade-offs and best practices for achieving reliability in real-world applications. The findings emphasize the importance of addressing vulnerabilities related to adversarial attacks and data noise.