A generalization of the steepest descent method for matrix functions.
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A method for dealing with ill-conditioned symmetric linear systems
Petr Liebl, Markéta Nováková (1970)
Aplikace matematiky
A note on Newbery's algorithm for discrete least-squares approximation by trigonometric polynomials.
Faßbender, Heike (1996)
ETNA. Electronic Transactions on Numerical Analysis [electronic only]
A proximal ANLS algorithm for nonnegative tensor factorization with a periodic enhanced line search
Douglas Bunker, Lixing Han, Shu Hua Zhang (2013)
Applications of Mathematics
The Alternating Nonnegative Least Squares (ANLS) method is commonly used for solving nonnegative tensor factorization problems. In this paper, we focus on algorithmic improvement of this method. We present a Proximal ANLS (PANLS) algorithm to enforce convergence. To speed up the PANLS method, we propose to combine it with a periodic enhanced line search strategy. The resulting algorithm, PANLS/PELS, converges to a critical point of the nonnegative tensor factorization problem under mild conditions....
Alcune osservazioni sul rango numerico per operatori non lineari
Jürgen Appell, G. Conti, Paola Santucci (1999)
Mathematica Bohemica
We discuss some numerical ranges for Lipschitz continuous nonlinear operators and their relations to spectral sets. In particular, we show that the spectrum defined by Kachurovskij (1969) for Lipschitz continuous operators is contained in the so-called polynomial hull of the numerical range introduced by Rhodius (1984).
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