In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
—As more and more real-world optimization problems become increasingly complex, algorithms with more capable optimizations are also increasing in demand. For solving large scale ...
Triangle counting is an important problem in graph mining. Two frequently used metrics in complex network analysis which require the count of triangles are the clustering coefficie...
Large-scale 3D reconstruction has recently received much attention from the computer vision community. Bundle adjustment is a key component of 3D reconstruction problems. However,...