Weakening Covert Networks by Minimizing Inverse Geodesic Length

Authors: Haris Aziz, Serge Gaspers, Kamran Najeebullah

IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we undertake a study of the classical and parameterized complexity of the MINIGL problem. The problem is NP-complete even if T = 0 and remains both NP-complete and W[1]-hard for parameter k on bipartite and on split graphs. On the positive side, we design several multivariate algorithms for the problem. Our main result is an algorithm for MINIGL parameterized by twin cover number. Our main focus is a parameterized complexity analysis of the problem.
Researcher Affiliation Academia Haris Aziz, Serge Gaspers and Kamran Najeebullah Data61, CSIRO, Australia UNSW Sydney, Australia {haris.aziz, kamran.najeebullah}@data61.csiro.au, sergeg@cse.unsw.edu.au
Pseudocode Yes Algorithm 1: MINIGL parameterized by the size of a twin cover of the input graph.
Open Source Code No The paper does not mention releasing any source code for the methodology described.
Open Datasets Yes Table 1 shows five representative datasets of covert networks from [UCINET Software, 2017] with some parameter values. [UCINET Software, 2017] UCINET Software. Datasets: Covert networks, 2017. Retrieved from https:// sites.google.com/site/ucinetsoftware/ datasets/covert-networks on 2017-02-17.
Dataset Splits No The paper is theoretical and does not describe training, validation, or test dataset splits.
Hardware Specification No The paper is theoretical and does not describe hardware specifications for running experiments.
Software Dependencies No The paper is theoretical and does not provide specific ancillary software details with version numbers.
Experiment Setup No The paper is theoretical and does not provide details about an experimental setup.