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Aix-Marseille Université
Institut de Mathématiques de Marseille (I2M) - UMR 7373
Site Saint-Charles : 3 place Victor Hugo, Case 19, 13331 Marseille Cedex 3
Site Luminy : Campus de Luminy - Case 907 - 13288 Marseille Cedex 9

A random matrix framework for big data machine learning




Date(s) : 29/09/2017   iCal
14h00 - 15h00

Thanks to its efficiently exploiting degrees of freedom in large multi-dimensional problems, random matrix theory has today become a compelling field in modern (multi-antenna multi-user multi-cell) wireless communications and is currently making powerful headway into large dimensional signal processing and statistics. With the advent of the big data paradigm, challenging machine learning questions arise, which we claim random matrix theory can address like no other tool before.
In this talk, after a basic introduction and motivation to random matrix theory, we shall discuss our early findings in the theoretical understanding and the resulting practical improvements of kernel spectral clustering and semi-supervised learning for large dimensional data, community detection on large realistic graphs, and shall also briefly discuss neural networks as well as robust statistics applications.

http://romaincouillet.hebfree.org

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