arXiv cs.CV July 10, 2026 · Papers

Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures

arXiv:2607.08511v1 Announce Type: cross Abstract: Choosing a learning rate scheduling strategy is critical to neural network training, but manual selection is costly and rarely exhaustive. While classical AutoML approaches often treat the scheduler as a secondary hyperparameter, we systematically investigate its impact