Timur Dali Purwanto

Multi-Objective Optimization in Machine Learning for Balancing Accuracy, Fairness and Efficiency

A multi-objective optimization framework that simultaneously integrates accuracy, fairness, and efficiency within the model development process using Pareto-based optimization techniques is proposed, enabling the development of models that are not only accurate but also fair and efficient.