It has been recently shown that a large class of balanced graph cuts allows for an exact relaxation into a nonlinear eigenproblem. We review briefly some of these results and propose a family of algorithms to compute nonlinear eigenvectors which encompasses previous work as special cases. We provide a detailed analysis of the properties and the convergence behavior of these algorithms and then ...

We consider the random graph induced by the random key predistribution scheme of Eschenauer and Gligor under the assumption of full visibility. We show the existence of a zero-one law for the absence of isolated nodes, and complement it by a Poisson convergence for the number of isolated nodes. Leveraging earlier results and analogies with Erdős-Renyi graphs, we explore similar results for the ...

We propose a method called Topic Graph based NMF for Transfer Learning (TNT) based on Non-negative Matrix Factorization (NMF). Since NMF learns feature vectors to approximate the given data, the proposed approach tries to preserve the feature space which is spanned by the feature vectors to realize transfer learning. Based on the learned feature vectors in the source domain, a graph structure c...

Fault detection and isolation is an area of engineering dealing with designing online protocols for systems that allow one to identify the existence faults, pinpoint their exact location, overcome them. We consider multi-agent systems, where faults correspond disappearance links in underlying graph, simulating communication failures between agents. study case which agents controllers are maxima...

This paper describes a news summarization system using the Fuzzy Graph based Document Model. News articles are modelled as fuzzy graphs whose nodes are sentences and edges are weighted by the fuzzy similarity measure between the sentences. The similarity between sentences is in between 0 and 1. Centrality of the graph retrieves important sentences. The proposed system produces summaries by Eige...

We propose certain Durrmeyer-type operators for Apostol-Genocchi polynomials in this research. We explore these operators' approximation attributes and measure the rate of convergence. In addition, we present a direct theorem based on first second-order modulus continuity, local findings Lipschitz class functions typical continuity. Finally, showed graph illustratin...

A regularized optimization problem over a large unstructured graph is studied, where the regularization term is tied to the graph geometry. Typical regularization examples include the total variation and the Laplacian regularizations over the graph. When applying the proximal gradient algorithm to solve this problem, there exist quite affordable methods to implement the proximity operator (back...

This note studies a network of agents having continuous-time dynamics with quantized interactions and time-varying directed topology. Due to the discontinuity of the dynamics, solutions of the resulting ODE system are intended in the sense of Krasovskii. A limit connectivity graph is defined, which encodes persistent interactions between nodes: if such graph has a globally reachable node, Kraso...

We investigate collaborative optimization in a multi-agent setting, when the agents execute in a distributed manner using local information, while the communication topology used to exchange messages and information is modeled by a graph-valued random process, independent of other time instances. Specifically, we study the performance of the consensus-based multi-agent subgradient method, for t...