What is the role of annealing in optimization-based dimensionality reduction?

Annealing gradually reduces optimization parameters to stabilize convergence.

Annealing strategies, such as reducing learning rates or KL weights over time, help optimization-based DR methods avoid poor local minima. In t-SNE and VAEs, annealing controls how strongly certain forces or constraints influence early vs late training.