We study stable matchings on exogenously given or endogenously formed bipartite graphs that reflect constraints on matching. The effects of a change of the exogenously given graph (constraints) are investigated. Specifically, we examine to what extent individuals gain or lose from relaxing...

The communities in a network have distinct characteristics and interrelationships. Community discovery methods based on node embedding and deep learning have surpassed spectral clustering and statistical inference as the preferred methods for handling high-dimensional network data. Community...

A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...

Since the 2008 economic crisis, network research has become increasingly prominent in the world of finance. The complex interrelations and financial interdependencies formed among financial market participants have proved to be critical in times of crisis. In this paper, we explore the network...