Adamczewski, Kamil Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;
https://doi.org/10.1109/CVPR52688.2022.00029 (Publisher version)
https://doi.org/10.48550/arXiv.2205.05676 (Preprint)
https://openaccess.thecvf.com/content/CVPR2022/papers/Li_Revisiting_Random_Channel_Pruning_for_Neural_Network_Compression_CVPR_2022_paper.pdf (Publisher version)
Li, Y., Adamczewski, K., Li, W., Gu, S., Timofte, R., & Van Gool, L. (2022). Revisiting Random Channel Pruning for Neural Network Compression. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 191-201). Piscataway, NJ: IEEE. doi:10.1109/CVPR52688.2022.00029.