... the graph signal processing framework as follows: graph theory random data on graphs big data on graphs signal processing on graphs machine learning on graphs graph topology learning systems on graphs vertex-frequency estimation graph neural networks graphs and tensors Graphs...

... domains (such as social networks, various ad-hoc sensor networks). Yet, despite the long history of Graph Theory, current approaches tend to focus on aspects of optimisation of graphs themselves rather than on eliciting strategies relevant to the objective application of the graph paradigm...

... into financial data analysis (the investment analysis), by means of portfolio cuts; (ii) London underground transportation system. The latter example demonstrates how graph theory can be used to identify the stations in the London underground network which have the greatest influence on the functionality...