Revisiting Structured Dropout. (arXiv:2210.02570v1 [cs.LG])

Large neural networks are often overparameterised and prone to overfitting,
Dropout is a widely used regularization technique to combat overfitting and
improve model generalization. However, unstructured Dropout is not always
effective for specific network architectures and this has led to the formation
of multiple structured Dropout approaches to improve model performance and,
sometimes, reduce the computational resources required for inference. In this
work, we revisit structured Dropout comparing different Dropout approaches to
natural language processing and computer vision tasks for …

arxiv dropout