Progressive Training

Progressive training is a machine learning technique that incrementally builds model complexity or optimizes parameters over multiple stages, aiming to improve training efficiency, stability, and generalization. Current research focuses on applying this approach to diverse areas, including federated learning, multimodal learning, and various neural network architectures (e.g., GANs, Transformers), often incorporating layer-wise training or curriculum learning strategies. This methodology offers significant potential for reducing computational costs, enhancing model robustness, and improving performance in resource-constrained environments or complex tasks like few-shot learning and video generation.