SageDy: A Novel Sampling and Aggregating Based Representation Learning Approach for Dynamic Networks

Jiaming Wu, Meng Liu, Jiangting Fan, Yong Liu, Meng Han. SageDy: A Novel Sampling and Aggregating Based Representation Learning Approach for Dynamic Networks. In Igor Farkas, Paolo Masulli, Sebastian Otte, Stefan Wermter, editors, Artificial Neural Networks and Machine Learning - ICANN 2021 - 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part V. Volume 12895 of Lecture Notes in Computer Science, pages 3-15, Springer, 2021. [doi]

@inproceedings{WuLFLH21,
  title = {SageDy: A Novel Sampling and Aggregating Based Representation Learning Approach for Dynamic Networks},
  author = {Jiaming Wu and Meng Liu and Jiangting Fan and Yong Liu and Meng Han},
  year = {2021},
  doi = {10.1007/978-3-030-86383-8_1},
  url = {https://doi.org/10.1007/978-3-030-86383-8_1},
  researchr = {https://researchr.org/publication/WuLFLH21},
  cites = {0},
  citedby = {0},
  pages = {3-15},
  booktitle = {Artificial Neural Networks and Machine Learning - ICANN 2021 - 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part V},
  editor = {Igor Farkas and Paolo Masulli and Sebastian Otte and Stefan Wermter},
  volume = {12895},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-86383-8},
}