In this paper, we propose a novel clustering algorithm for Design Structure Matrices (DSMs) with the goal of providing a balanced system partitioning. DSMs are one of the standard forms of modeling ...

Recent demands on data privacy have called for federated learning (FL) as a new distributed learning paradigm in massive and heterogeneous networks. Although many FL algorithms have been proposed, few ...

Learn how to use the Design Structure Matrix (DSM) to visualize, communicate, and manage the dependencies between the elements of a system, and to perform various analyses to improve the system ...

Many real-world datasets are comprised of different representations or views which often provide information complementary to each other. To integrate information from multiple views in the ...

Bi-clusters can thus be seen as sub-matrices of a matrix representing features of elements. It should be noted that bi-clusters need not to be exclusive nor exhaustive (Xhafa et al., 2011).The ...

Multi-view clustering algorithms have emerged as a pivotal area of machine learning research, designed to integrate and exploit diverse sources of data depiction. By utilising multiple views or ...

Kruskal's algorithm and the union find data structure applied to the clustering problem as presented in week 2 of Tim Roughgarden's Stanford Online course entitled, "Greedy Algorithms, Minimum ...