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pro vyhledávání: '"Stephen A. Vavasis"'
Autor:
Stephen A. Vavasis, Xuan Vinh Doan
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030218027
WCGO
WCGO
We propose Ky Fan 2-k-norm-based models for the nonconvex low-rank matrix recovery problem. A general difference of convex algorithm (DCA) is developed to solve these models. Numerical results show that the proposed models achieve high recoverability
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abe8ead5bd63585bfc2fa0f0597d0c65
https://doi.org/10.1007/978-3-030-21803-4_32
https://doi.org/10.1007/978-3-030-21803-4_32
Cohesive fracture is among the few techniques able to model complex fracture nucleation and propagation with a sharp (nonsmeared) representation of the crack. Implicit time-stepping schemes are often favored in mechanics due to their ability to take
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53cbb5007f085844479a95bde1c090fd
Autor:
Nicolas Gillis, Stephen A. Vavasis
Publikováno v:
SIAM Journal on Optimization. 25:677-698
Nonnegative matrix factorization (NMF) under the separability assumption can provably be solved efficiently, even in the presence of noise, and has been shown to be a powerful technique in document classification and hyperspectral unmixing. This prob
Autor:
Stephen A. Vavasis, Nicolas Gillis
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 36:698-714
In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns), which is equiv
Autor:
Stephen A. Vavasis, Xuan Vinh Doan
Publikováno v:
SIAM Journal on Optimization. 23:2502-2540
We propose a convex optimization formulation with the nuclear norm and $\ell_1$-norm to find a large approximately rank-one submatrix of a given nonnegative matrix. We develop optimality conditions for the formulation and characterize the properties
Publikováno v:
SIAM Journal on Scientific Computing. 35:A517-A540
We propose a proximal point algorithm to solve the LAROS problem, that is, the problem of finding a “large approximately rank-one submatrix.” This LAROS problem is used to sequentially extract features in data. We also develop new stopping criter
Publikováno v:
Engineering with Computers. 30:315-329
The presence of a few inverted or poor-quality mesh elements can negatively affect the stability, convergence and efficiency of a finite element solver and the accuracy of the associated partial differential equation solution. We propose a mesh quali
Autor:
Suzanne M. Shontz, Stephen A. Vavasis
Publikováno v:
Engineering with Computers. 28:135-147
Compressible Mooney-Rivlin theory has been used to model hyperelastic solids, such as rubber and porous polymers, and more recently for the modeling of soft tissues for biomedical tissues, undergoing large elastic deformations. We propose a solution
Autor:
Brendan P. W. Ames, Stephen A. Vavasis
Publikováno v:
Mathematical Programming. 129:69-89
We consider the problems of finding a maximum clique in a graph and finding a maximum-edge biclique in a bipartite graph. Both problems are NP-hard. We write both problems as matrix-rank minimization and then relax them using the nuclear norm. This t
Publikováno v:
SIAM Journal on Numerical Analysis. 46:3264-3284
We consider linear systems arising from the use of the finite element method for solving scalar linear elliptic problems. Our main result is that these linear systems, which are symmetric and positive semidefinite, are well approximated by symmetric