Abstract: We propose graph-driven approaches to image segmentation by developing diffusion processes defined on arbitrary graphs. We formulate a solution to the image segmentation problem modeled as ...

Abstract: Coloring for random graph from G(n,1/2) is a classic example exhibiting an Information v. Computation gap: it has chromatic number of Theta(n/log n) w.p. 1-o(1) while the best efficiently ...

Discrete structures are omnipresent in mathematics, computer science, statistical physics, optimisation and models of natural phenomena. For instance, complex random graphs serve as a model for social ...

As mathematical abstractions go, graphs are among the simplest. Scatter a bunch of points in a plane. Connect some of them with lines. That’s all a graph is. And yet they are incredibly powerful. They ...

Want to create beautiful animated charts or graphs? Here are the best free online graph and chart maker tools that let you generate animated graphs online. These websites provide a feature to ...

Ramsey problems, such as r(4,5) are simple to state, but as shown in this graph, the possible solutions are nearly endless, making them very difficult to solve. (cr: Jacques Verstraete) We’ve all been ...

Reasoning about graphs, and learning from graph data is a field of artificial intelligence that has recently received much attention in the machine learning areas of graph representation learning and ...

Abstract: Distributed consensus computation over random graph processes is considered. The random graph process is defined as a sequence of random variables which take values from the set of all ...