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Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
[article]
2022
arXiv
pre-print
Works on lottery ticket hypothesis (LTH) and single-shot network pruning (SNIP) have raised a lot of attention currently on post-training pruning (iterative magnitude pruning), and before-training pruning (pruning at initialization). The former method suffers from an extremely large computation cost and the latter usually struggles with insufficient performance. In comparison, during-training pruning, a class of pruning methods that simultaneously enjoys the training/inference efficiency and
arXiv:2106.10404v4
fatcat:p5jb643ykvdj5mqexsx434wv7a