To prune, or not to prune: exploring the efficacy of pruning for model compression — mentioned by ekelsen

Sat, 07 Mar 2020 15:55:04 GMT

The implications are unclear to me. We already know how to prune models for inference. For example https://arxiv.org/abs/1710.01878, along with earlier work (and more recent work). There's also work showing that you can take advantage of the sparsity to achieve practical speed gains: https://arxiv.org/abs/1911.09723. We can also train networks that are sparse from the beginning of training (without requiring any special knowledge of the solution): https://arxiv.org/abs/1911.11134. It remains to be shown that this can be done with a speed advantage.

Paper and discussion history. A mention is not an endorsement.

To prune, or not to prune: exploring the efficacy of pruning for model compression · HackerPapers discussions

To prune, or not to prune: exploring the efficacy of pruning for model compression — mentioned by ekelsen