Tensor train completion: Local recovery guarantees via Riemannian optimization

In this work, we estimate the number of randomly selected elements of a tensor that with high probability guarantees local convergence of Riemannian gradient descent for tensor train completion. We derive a new bound for the orthogonal projections onto the tangent spaces based on the harmonic mean o...

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Veröffentlicht in:	Numerical linear algebra with applications 2023-12, Vol.30 (6)
Hauptverfasser:	Budzinskiy, Stanislav, Zamarashkin, Nikolai
Format:	Artikel
Sprache:	eng
Schlagworte:	Convergence Mathematical analysis Optimization Tensors
Online-Zugang:	Volltext
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