Movement Pruning
Movement Pruning
**Movement Pruning** is a simple, deterministic first-order weight pruning method that is more adaptive to pretrained model fine-tuning. Magnitude pruning can be seen as utilizing zeroth-order information (absolute value) of the running model. In contrast, movement pruning methods are where importance is derived from first-order information. Intuitively, instead of selecting weights that are far from zero, we retain connections that are moving away from zero during the training process.
Movement Pruning: Adaptive Sparsity by Fine-Tuning
https://paperswithcode.com/paper/movement-pruning-adaptive-sparsity-by-fine
Movement Pruning: Adaptive Sparsity by Fine-Tuning