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

Angelina Brilliantova; Ivona Bezáková

AAAI 2023technical0 citations

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

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.

BibTeX

@article{Brilliantova_Bezáková_2024, title={Model Selection of Graph Signage Models Using Maximum Likelihood (Student Abstract)}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26944}, DOI={10.1609/aaai.v37i13.26944}, abstractNote={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.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Brilliantova, Angelina and Bezáková, Ivona}, year={2024}, month={Jul.}, pages={16168-16169} }