Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications

Pin-Yu Chen, Lingfei Wu, Sijia Liu 0001, Indika Rajapakse. Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications. In Kamalika Chaudhuri, Ruslan Salakhutdinov, editors, Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA. Volume 97 of Proceedings of Machine Learning Research, pages 1091-1101, PMLR, 2019. [doi]

@inproceedings{ChenW0R19,
  title = {Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications},
  author = {Pin-Yu Chen and Lingfei Wu and Sijia Liu 0001 and Indika Rajapakse},
  year = {2019},
  url = {http://proceedings.mlr.press/v97/chen19j.html},
  researchr = {https://researchr.org/publication/ChenW0R19},
  cites = {0},
  citedby = {0},
  pages = {1091-1101},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA},
  editor = {Kamalika Chaudhuri and Ruslan Salakhutdinov},
  volume = {97},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}