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                <term xml:lang="en">Canonical polyadic decomposition</term>
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              <p>The canonical polyadic decomposition is one of the most used tensor decomposition. However classical decomposition algorithms such as alternating least squares suffer from convergence problems and thus the decomposition of large ten-sors can be very time consuming. Recently it has been shown that the decomposition can be rewritten as a joint eigenvalue decomposition problem. In this paper we propose a fast joint eigenvalue decomposition algorithm then we show how it can benefit the canonical polyadic decomposition of large tensors.</p>
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              <p>La decomposizione canonica di tensorì e usata in diversi campi tra cui quello dei data sciences. Tuttavia, in classici algoritmi di decomposizione, come l'alternating least squares, si possono riscontrare problemi di convergenza e pro-prio per questo motivo che la decomposizione di grandi tensori puo essere molto dispendiosa in termini di tempo di calcolo. Recentemente, sono stati sviluppati al-goritmi di decomposizione canonica veloci, basati sulla diagonalizzazione di un in-sieme di matrici su una base comune di autovettori. In questo articolo proponiamo un algoritmo originale per risolvere quest'ultimo problema. In seguito mettiamo in evidenza l'aspettopì u interessante di questo approccio al fine di effettuare la de-composizione canonica di grandi tensori.</p>
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