Local Network Community Detection: K-means Clustering and Conductance

Twan van Laarhoven

Radboud University Nijmegen, The Netherlands

11 November 2016, 2:30 pm


Local network community detection is the task of finding a single community of nodes concentrated around few given seed nodes in a localized way. Conductance is a popular objective function used in many algorithms for local community detection. In this talk I will introduce a continuous relaxation of conductance. I will show that continuous optimization of this objective still leads to discrete communities. I investigate the relation of conductance with weighted kernel k-means for a single community, which leads to the introduction of a new objective function, σ-conductance. Conductance is obtained by setting σ to 0.

Bio sketch

Twan van Laarhoven is a postdoctoral researcher at the Data Science group of the Radboud University Nijmegen, the Netherlands. In 2015 he completed his PhD thesis on networks for machine learning, also at the Radboud University. Twan has a broad research interest in machine learning, with a focus on network analysis, clustering, and deep learning.

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