Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach

M. Maruf, Anuj Karpatne. Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach. In Carlotta Demeniconi, Ian Davidson, editors, Proceedings of the 2021 SIAM International Conference on Data Mining, SDM 2021, Virtual Event, April 29 - May 1, 2021. pages 271-279, SIAM, 2021. [doi]

@inproceedings{MarufK21,
  title = {Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach},
  author = {M. Maruf and Anuj Karpatne},
  year = {2021},
  doi = {10.1137/1.9781611976700.31},
  url = {https://doi.org/10.1137/1.9781611976700.31},
  researchr = {https://researchr.org/publication/MarufK21},
  cites = {0},
  citedby = {0},
  pages = {271-279},
  booktitle = {Proceedings of the 2021 SIAM International Conference on Data Mining, SDM 2021, Virtual Event, April 29 - May 1, 2021},
  editor = {Carlotta Demeniconi and Ian Davidson},
  publisher = {SIAM},
  isbn = {978-1-61197-670-0},
}