Fetching the paper…
Reading the bibliography…
This work proposes a novel Graph-based neural ArchiTecture Encoding Scheme, a.k.a.
Sen, P.K.: Estimates of the regression coefficient based on kendall’s tau. Journal of the American statistical association 63
1968
Earlier work this paper cites.
Stagge, P., Igel, C.: Neural network structures and isomorphisms: Random walk characteristics of the search space. In: 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks. Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (Cat. No. 00. pp. 82–90. IEEE (2000)
2000
Earlier work this paper cites.
Shashua, A., Levin, A.: Ranking with large margin principle: Two approaches. In: Advances in neural information processing systems. pp. 961–968 (2003)
2003
Earlier work this paper cites.
Burges, C., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., Hullender, G.: Learning to rank using gradient descent. In: Proceedings of the 22nd international conference on Machine learning. pp. 89–96 (2005)
2005
Earlier work this paper cites.
Xia, F., Liu, T.Y., Wang, J., Zhang, W., Li, H.: Listwise approach to learning to rank: theory and algorithm. In: Proceedings of the 25th international conference on Machine learning. pp. 1192–1199 (2008)
2008
Earlier work this paper cites.
Chen, W., yan Liu, T., Lan, Y., ming Ma, Z., Li, H.: Ranking measures and loss functions in learning to rank. In: Bengio, Y., Schuurmans, D., Lafferty, J.D., Williams, C.K.I., Culotta, A. (eds.) Advances in Neural Information Processing Systems 22, pp. 315–323. Curran Associates, Inc. (2009)
2009
Earlier work this paper cites.
Liu, T.Y., et al.: Learning to rank for information retrieval. Foundations and Trends® in Information Retrieval 3
2009
Earlier work this paper cites.
Guo, Y., Chen, Y., Zheng, Y., Zhao, P., Chen, J., Huang, J., Tan, M.: Breaking the curse of space explosion: Towards effcient nas with curriculum search. In: International Conference on Machine Learning (2010)
2010
Earlier work this paper cites.
2014
Earlier work this paper cites.
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Kandasamy, K., Neiswanger, W., Schneider, J., Poczos, B., Xing, E.P.: Neural architecture search with bayesian optimisation and optimal transport. In: Advances in Neural Information Processing Systems. pp. 2016–2025 (2018)
2018
Cited alongside, same era.
Liu, C., Zoph, B., Neumann, M., Shlens, J., Hua, W., Li, L.J., Fei-Fei, L., Yuille, A., Huang, J., Murphy, K.: Progressive neural architecture search. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 19–34 (2018)
2018
Cited alongside, same era.
Guo, Y., Zheng, Y., Tan, M., Chen, Q., Chen, J., Zhao, P., Huang, J.: Nat: Neural architecture transformer for accurate and compact architectures. In: Advances in Neural Information Processing Systems. pp. 735–747 (2019)
2019
Later among the works it cites.
2019
Later among the works it cites.
Real, E., Aggarwal, A., Huang, Y., Le, Q.V.: Regularized evolution for image classifier architecture search. In: Proceedings of the aaai conference on artificial intelligence. vol. 33, pp. 4780–4789 (2019)
2019
Later among the works it cites.
2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2018
Cited alongside, same era.
Luo, R., Tian, F., Qin, T., Chen, E., Liu, T.Y.: Neural architecture optimization. In: Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N., Garnett, R. (eds.) Advances in Neural Information Processing Systems 31, pp. 7816–7827. Curran Associates, Inc. (2018), http://papers.nips.cc/paper/8007-neural-architecture-optimization.pdf
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2019
Later among the works it cites.
Xie, S., Kirillov, A., Girshick, R., He, K.: Exploring randomly wired neural networks for image recognition. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 1284–1293 (2019)
2019
Later among the works it cites.
Xu, Y., Wang, Y., Han, K., Jui, S., Xu, C., Tian, Q., Xu, C.: Renas:relativistic evaluation of neural architecture search (2019)
2019
Later among the works it cites.
2019
Later among the works it cites.
Dong, X., Yang, Y.: Nas-bench-201: Extending the scope of reproducible neural architecture search. In: International Conference on Learning Representations (2020), https://openreview.net/forum?id=HJxyZkBKDr
2020
Closest in time.
Lian, D., Zheng, Y., Xu, Y., Lu, Y., Lin, L., Zhao, P., Huang, J., Gao, S.: Towards fast adaptation of neural architectures with meta learning. In: International Conference on Learning Representations (2020)
2020
Closest in time.