Net2Net: Accelerating learning via knowledge transfer
Chen, T., Goodfellow, I., and Shlens, J. (2016) · 2016
Cited alongside, same era.
Deep Learning
Goodfellow, I., Bengio, Y., and Courville, A. (2016) · 2016
Cited alongside, same era.
Network morphism
Wei, T., Wang, C., Rui, Y., and Chen, C. W. (2016) · 2016
Cited alongside, same era.
Pruning filters for efficient convnets
Li, H., Kadav, A., Durdanovic, I., Samet, H., and Graf, H. P. (2017) · 2017
Cited alongside, same era.
Escaping flat areas via function-preserving structural network modifications
Kilcher, Y., Bécigneul, G., and Hofmann, T. (2018) · 2018
Cited alongside, same era.
NeST: A neural network synthesis tool based on a grow-and-prune paradigm
Dai, X., Yin, H., and Jha, N. K. (2019) · 2019
Cited alongside, same era.
Efficient network construction through structural plasticity
Du, X., Li, Z., Ma, Y., and Cao, Y. (2019) · 2019
Cited alongside, same era.
Neural architecture search: A survey
Elsken, T., Metzen, J. H., and Hutter, F. (2019) · 2019
Cited alongside, same era.
Splitting steepest descent for growing neural architectures
Wu, L., Wang, D., and Liu, Q. (2019) · 2019
Cited alongside, same era.
Model compression and hardware acceleration for neural networks: A comprehensive survey
Deng, L., Li, G., Han, S., Shi, L., and Xie, Y. (2020) · 2020
Cited alongside, same era.
FBNetV2: Differentiable neural architecture search for spatial and channel dimensions
Wan, A., Dai, X., Zhang, P., He, Z., Tian, Y., Xie, S., Wu, B., Yu, M., Xu, T., Chen, K., et al. (2020) · 2020
Cited alongside, same era.