From 2D to 3D: AISG-SLA Visual Localization Challenge
Abstract
The Clique Interdiction Problem (CIP) aims to minimize the size of the largest clique in a given graph by removing a given number of vertices. The CIP models a special Stackelberg game and has important applications in fields such as pandemic control and terrorist identification. However, the CIP is a bilevel graph optimization problem, making it very challenging to solve. Recently, data reduction techniques have been successfully applied in many (single-level) graph optimization problems like vertex cover. Motivated by this, we investigate a set of novel reduction rules and design a reduction-based algorithm, RECIP, for practically solving the CIP. RECIP enjoys an effective preprocessing procedure that systematically reduces the input graph, making the problem much easier to solve. Extensive experiments on 124 large real-world networks demonstrate the superior performance of RECIP and validate the effectiveness of the proposed reduction rules.
Cite
Text
Gao et al. "From 2D to 3D: AISG-SLA Visual Localization Challenge." International Joint Conference on Artificial Intelligence, 2024. doi:10.24963/ijcai.2024/1003Markdown
[Gao et al. "From 2D to 3D: AISG-SLA Visual Localization Challenge." International Joint Conference on Artificial Intelligence, 2024.](https://mlanthology.org/ijcai/2024/gao2024ijcai-d/) doi:10.24963/ijcai.2024/1003BibTeX
@inproceedings{gao2024ijcai-d,
title = {{From 2D to 3D: AISG-SLA Visual Localization Challenge}},
author = {Gao, Jialin and Ong, Bill and Lwi, Darld and Ng, Zhen Hao and Yee, Xun Wei and Mak, Mun-Thye and Ng, Wee Siong and Ng, See-Kiong and Teo, Hui Ying and Khoo, Victor and Bökman, Georg and Edstedt, Johan and Brodt, Kirill and Boittiaux, Clémentin and Ferrera, Maxime and Konev, Stepan},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2024},
pages = {8661-8664},
doi = {10.24963/ijcai.2024/1003},
url = {https://mlanthology.org/ijcai/2024/gao2024ijcai-d/}
}