1 citations · 1 across the 7 of their papers we have counts for
7 papers
GLL-type Nonmonotone Descent Methods Revisited under Kurdyka-Łojasiewicz Property
Yitian Qian, Ting Tao, Shaohua Pan +1
The purpose of this paper is to extend the full convergence results of the classic GLL-type (Grippo-Lampariello-Lucidi) nonmonotone methods to nonconvex and nonsmooth optimization.…
Convergence of ZH-type nonmonotone descent method for Kurdyka-Łojasiewicz optimization problems
Yitian Qian, Ting Tao, Shaohua Pan +1
We propose a novel iterative framework for minimizing a proper lower semicontinuous Kurdyka-Łojasiewicz (KL) function . It comprises a Zhang-Hager (ZH-type) nonmonotone decrease…
Convergence of the majorized PAM method with subspace correction for low-rank composite factorization model
Ting Tao, Yitian Qian, Shaohua Pan
This paper focuses on the convergence certificates of the majorized proximal alternating minimization (PAM) method with subspace correction, proposed in \cite{TaoQianPan22} for the…
An inexact LPA for DC composite optimization and application to matrix completions with outliers
Ting Tao, Ruyu Liu, Shaohua Pan
This paper concerns a class of DC composite optimization problems which, as an extension of convex composite optimization problems and DC programs with nonsmooth components, often…
Column -norm regularized factorization model of low-rank matrix recovery and its computation
Ting Tao, Yitian Qian, Shaohua Pan
This paper is concerned with the column -regularized factorization model of low-rank matrix recovery problems and its computation. The column -norm of facto…
Error bound of critical points and KL property of exponent for squared F-norm regularized factorization
Ting Tao, Shaohua Pan, Shujun Bi
This paper is concerned with the squared F(robenius)-norm regularized factorization form for noisy low-rank matrix recovery problems. Under a suitable assumption on the restricted…
Calibrated zero-norm regularized LS estimator for high-dimensional error-in-variables regression
Ting Tao, Shaohua Pan, Shujun Bi
This paper is concerned with high-dimensional error-in-variables regression that aims at identifying a small number of important interpretable factors for corrupted data from many…