ML Anthology

Model Selection of Graph Signage Models Using Maximum Likelihood (Student Abstract)

Angelina Brilliantova, Ivona Bezáková
AAAI 2023 pp. 16168-16169
doi:10.1609/AAAI.V37I13.26944 /aaai/2023/brilliantova2023aaai-model/

Abstract

Complex systems across various domains can be naturally modeled as signed networks with positive and negative edges. In this work, we design a new class of signage models and show how to select the model parameters that best fit real-world datasets using maximum likelihood.

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Cite

Text

Brilliantova and Bezáková. "Model Selection of Graph Signage Models Using Maximum Likelihood (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.26944

Markdown

[Brilliantova and Bezáková. "Model Selection of Graph Signage Models Using Maximum Likelihood (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/brilliantova2023aaai-model/) doi:10.1609/AAAI.V37I13.26944

BibTeX

@inproceedings{brilliantova2023aaai-model,
  title     = {{Model Selection of Graph Signage Models Using Maximum Likelihood (Student Abstract)}},
  author    = {Brilliantova, Angelina and Bezáková, Ivona},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {16168-16169},
  doi       = {10.1609/AAAI.V37I13.26944},
  url       = {https://mlanthology.org/aaai/2023/brilliantova2023aaai-model/}
}