Fetching the paper…
Reading the bibliography…
The power law has been observed in the degree distributions of many biological neural networks.
B. D. Malamud, G. Morein, and D. L. Turcotte, “Forest fires: An example of self-organized critical behavior,” Science , vol. 281, no. 5384, pp. 1840–1842, 1998
1998
Earlier work this paper cites.
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proceedings of the IEEE , vol. 86, no. 11, pp. 2278–2324, 1998
1998
Earlier work this paper cites.
A. L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science , vol. 286, no. 5439, pp. 509–512, 1999
1999
Earlier work this paper cites.
L. A. N. Amaral, A. Scala, M. Barthelemy, and H. E. Stanley, “Classes of small-world networks,” Proceedings of the National Academy of Sciences , vol. 97, no. 21, pp. 11 149–11 152, 2000
2000
Earlier work this paper cites.
S. M. Burroughs and S. F. Tebbens, “Upper-truncated power laws in natural systems,” Pure and Applied Geophysics , vol. 158, no. 4, pp. 741–757, 2001
2001
Earlier work this paper cites.
A. Barabâsi, H. Jeong, Z. Néda, E. Ravasz, A. Schubert, and T. Vicsek, “Evolution of the social network of scientific collaborations,” Physica A: Statistical Mechanics and its Applications , vol. 311, no. 3, pp. 590–614, 2002
2002
Earlier work this paper cites.
V. M. Eguiluz, D. R. Chialvo, G. A. Cecchi, M. Baliki, and A. V. Apkarian, “Scale-free brain functional networks,” Physical Review Letters , vol. 94, no. 1, p. 018102, 2005
2005
Earlier work this paper cites.
Y. Iturria-Medina, R. C. Sotero, E. J. Canales-Rodríguez, Y. Alemán-Gómez, and L. Melie-García, “Studying the human brain anatomical network via diffusion-weighted mri and graph theory,” Neuroimage , vol. 40, no. 3, pp. 1064–1076, 2008
2008
Earlier work this paper cites.
A. Clauset, C. R. Shalizi, and M. E. J. Newman, “Power-law distributions in empirical data,” SIAM Review , vol. 51, no. 4, pp. 661–703, 2009
2009
Cited alongside, same era.
M. L. Anderson, “Neural reuse: A fundamental organizational principle of the brain,” Behavioral and Brain Sciences , vol. 33, no. 4, pp. 245–266, 2010
2010
Cited alongside, same era.
D. Kolyukhin and A. Torabi, “Power-law testing for fault attributes distributions,” Pure and Applied Geophysics , vol. 170, no. 12, pp. 2173–2183, 2013
2013
Cited alongside, same era.
2013
Cited alongside, same era.
Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature , vol. 521, no. 7553, pp. 436–444, 2015
S. Han, H. Mao, and W. J. Dally, “Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding,” in International Conference of Learning Representations , 2016
2016
Later among the works it cites.
H. Li, A. Kadav, I. Durdanovic, H. Samet, and H. P. Graf, “Pruning filters for efficient convnets,” in International Conference of Learning Representations , 2017
2017
Later among the works it cites.
J. Kirkpatrick, R. Pascanu, N. Rabinowitz, J. Veness, G. Desjardins, A. A. Rusu, K. Milan, J. Quan, T. Ramalho, A. Grabska-Barwinska et al. , “Overcoming catastrophic forgetting in neural networks,” Proceedings of the National Academy of Sciences , vol. 114, no. 13, pp. 3521–3526, 2017
2017
Later among the works it cites.
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2015
Cited alongside, same era.
S. Han, J. Pool, J. Tran, and W. Dally, “Learning both weights and connections for efficient neural network,” in Advances in Neural Information Processing Systems , 2015, pp. 1135–1143
2015
Cited alongside, same era.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. Berg, and F.-F. Li, “ImageNet large scale visual recognition challenge,” International Journal of Computer Vision , vol. 115, no. 3, pp. 211–252, 2015
2015
Cited alongside, same era.
R. L. S. Monteiro, T. K. G. Carneiro, J. R. A. Fontoura, V. L. da Silva, M. A. Moret, and H. B. de Barros Pereira, “A model for improving the learning curves of artificial neural networks,” PloS One , vol. 11, no. 2, p. e0149874, 2016
2016
Cited alongside, same era.
R. Hanel, B. Corominas-Murtra, B. Liu, and S. Thurner, “Fitting power-laws in empirical data with estimators that work for all exponents,” PloS one , vol. 12, no. 2, p. e0170920, 2017
2017
Later among the works it cites.
F. Zenke, B. Poole, and S. Ganguli, “Continual learning through synaptic intelligence,” in International Conference on Machine Learning , 2017, pp. 3987–3995
2017
Later among the works it cites.
S. Han, J. Pool, S. Narang, H. Mao, S. Tang, E. Elsen, B. Catanzaro, J. Tran, and W. J. Dally, “DSD: Regularizing deep neural networks with dense-sparse-dense training flow,” in International Conference of Learning Representations , 2017
2017
Later among the works it cites.