What is multi-objective optimization in cost functions?

Multi-objective optimization combines multiple competing cost functions into a single training objective.

Real-world systems often require balancing multiple losses, such as accuracy, fairness, and efficiency. These are combined using weighted sums or Pareto optimization. Choosing weights is non-trivial and often requires hyperparameter tuning or adaptive balancing strategies.