The idea of minimum curvilinearity (MC) is that the hidden geometry of complex networks, in particular when they are sufficiently sparse, clustered, small-world and heterogeneous, can be efficiently navigated using the minimum spanning tree (MST), which is a greedy navigator. The local topological information drives the global geometrical navigation and the MST can be interpreted as a growing p...

This paper describes an experimental study of constraint-based network design. We used a novel network design tool, implemented in Java, to design representative networks joining major U.S. cities. The cost of three topologies: Best Star, Minimum Spanning Tree (MST), and Delaunay Triangulation, are compared, with and without localized tra c constraints. The best star network gives near optimal ...

The minimum spanning tree (MST) construction is a classical problem in Distributed Computing for creating a globally minimized structure distributedly. Self-stabilization is versatile technique for forward recovery that permits to handle any kind of transient faults in a unified manner. The loop-free property provides interesting safety assurance in dynamic networks where edge-cost changes duri...

We propose a non-local cost aggregation algorithm to recognize the identity of face and person tracks in a TV-series. In our approach, the fundamental element for identification is a track node, which is built on top of face and person tracks. Track nodes with temporal dependency are grouped into a knot. These knots then serve as the basic units in the construction of a k-knot graph for explori...

We present a new efficient localized algorithm to construct, for any given quasi-unit disk graph G = (V,E) and any ε > 0, a (1+ ε)spanner for G of maximum degree O(1) and total weight O(ω(MST )), where ω(MST ) denotes the weight of a minimum spanning tree for V . We further show that similar localized techniques can be used to construct, for a given unit disk graph G = (V,E), a planar Cdel(1+ε)...

Abstract—The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degr...

The initialization of the graph-based matching method depends on a minimum spanning tree (MST) parameterized by edge weights. Although we use the quadratic mean of mutual ranks as the edge weight, Structure-from-Motion (SfM) is not much affected by different weighting strategies, as we will show in the following experiment. It is shown that this method is not sensitive to the initial MST step. ...