Xiaohan Chen

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training

2022 · TU/e Research Portal

Random pruning is arguably the most naive way to attain sparsity in neural networks, but has been deemed uncompetitive by either post-training pruning or sparse training. In this paper, we focus on sparse training and …