Temporal networks, Tensors, and applications to ML

Докладчик: проф. Огнян Кунчев, ИМИ – БАН
Дата: 31.01.2024 г.
Час: 15:00 ч.
Място: …

Резюме: Recently, temporal networks got an increasing interest, related to their numerous applications in real-life data analysis. The temporal networks (more mathematically, “graphs depending on time”) are a typical example of a Tensor – the adjacency matrix depends on several parameters and is a tensor (in the mathematical sense of the word). We present some recent results about the structure of the spectrum of the normalized Laplacian in the case of “slowly varying temporal networks”. The detailed structure of the spectrum gives rise of the notion of “constant block Jacobi model”, which has closed-form solution for the spectrum and the eigenfunctions. This brings a reconsideration of the notion of Fiedler vector for temporal networks. Depending on the time, some discussion about the recent history of Tensors (mathematical sense) and their application in ML may be presented.

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