2013/02/04 by Brian Baingana, Georgios B. Giannakis, Baingana, Brian +1
Computer Science · Mathematics · Physics and Astronomy · #Complex Network Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #Data Visualization and Analytics #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Topological and Geometric Data Analysis #cs.CV #math.OC #stat.ML
paper · pdf · doi:10.48550/arxiv.1302.0870
Submitted to ICASSP May, 2013
arxiv created 2013/02/04 · openalex publication_date 2013/02/04 · arxiv updated 2013/02/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Visual rendering of graphs is a key task in the mapping of complex network data. Although most graph drawing algorithms emphasize aesthetic appeal, certain applications such as travel-time maps place more importance on visualization of structural network properties. The present paper advocates a graph embedding approach with centrality considerations to comply with node hierarchy. The problem is formulated as one of constrained multi-dimensional scaling (MDS), and it is solved via block coordinate descent iterations with successive approximations and guaranteed convergence to a KKT point. In addition, a regularization term enforcing graph smoothness is incorporated with the goal of reducing edge crossings. Experimental results demonstrate that the algorithm converges, and can be used to efficiently embed large graphs on the order of thousands of nodes.