Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee — mentioned by 317070

Wed, 13 Dec 2017 08:41:22 GMT

Compressing is indeed a hot topic, but I do feel like this article (the one on arXiv https://arxiv.org/abs/1611.05162 ) has some major shortcomings. First off, the datasets used (spiral and MNIST) are simple and small. They can be used as illustration, but should be avoided for benchmarking. Secondly, despite it being a hot topic, the authors did not compare with other algorithms. Thirdly, they have a 2 hidden dense layer network with over a million parameters for mnist, of course you can prune 95% of those parameters. You could probably have achieved the same result by simply training with…

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

Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee · HackerPapers discussions

Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee — mentioned by 317070