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Found 4 papers, 0 papers with code
An inexact LPA for DC composite optimization and application to matrix completions with outliers
For this class of nonconvex and nonsmooth problems, we propose an inexact linearized proximal algorithm (iLPA) by computing in each step an inexact minimizer of a strongly convex majorization constructed with a partial linearization of their objective functions at the current iterate, and establish the convergence of the generated iterate sequence under the Kurdyka-\L\"ojasiewicz (KL) property of a potential function.
Column $\ell_{2,0}$-norm regularized factorization model of low-rank matrix recovery and its computation
This paper is concerned with the column $\ell_{2, 0}$-regularized factorization model of low-rank matrix recovery problems and its computation.
Error bound of critical points and KL property of exponent $1/2$ for squared F-norm regularized factorization
This paper is concerned with the squared F(robenius)-norm regularized factorization form for noisy low-rank matrix recovery problems.
KL property of exponent $1/2$ of $\ell_{2,0}$-norm and DC regularized factorizations for low-rank matrix recovery
To cater for the scenario in which only a coarse estimation is available for the rank of the true matrix, an $\ell_{2, 0}$-norm regularized term is added to the factored loss function to reduce the rank adaptively; and account for the ambiguities in the factorization, a balanced term is then introduced.
