Imane Elmanaa

Adaptation-Preserving Structured Pruning for Efficient Transfer Learning in Deep Neural Networks

Transfer learning enables pretrained deep networks to adapt to new tasks but typically preserves their original computational structure, leaving much of the inference cost unchanged. Structured pruning can reduce this complexity; however, introducing sparsity during fine-tuning creates a competing optimization problem...