Zobrazeno 1 - 10
of 212
pro vyhledávání: '"YUJI NAKATSUKASA"'
Autor:
YUJI NAKATSUKASA, TROPP, JOEL A.
Publikováno v:
SIAM Journal on Matrix Analysis & Applications; 2024, Vol. 45 Issue 2, p1183-1214, 32p
Publikováno v:
SIAM Journal on Matrix Analysis & Applications; 2024, Vol. 45 Issue 2, p905-929, 25p
Publikováno v:
SIAM Journal on Scientific Computing; 2024, Vol. 46 Issue 2, pA929-A952, 24p
Publikováno v:
SIAM Journal on Matrix Analysis & Applications; 2024, Vol. 45 Issue 1, p619-633, 15p
Autor:
YUJI NAKATSUKASA, TAEJUN PARK
Publikováno v:
SIAM Journal on Matrix Analysis & Applications; 2023, Vol. 44 Issue 3, p1370-1392, 23p
Publikováno v:
SIAM Journal on Matrix Analysis & Applications; 2023, Vol. 44 Issue 3, p1245-1270, 26p
Publikováno v:
Mathematical Programming. 193:447-483
We present an algorithm for the minimization of a nonconvex quadratic function subject to linear inequality constraints and a two-sided bound on the 2-norm of its solution. The algorithm minimizes the objective using an active-set method by solving a
Autor:
BEHNAM HASHEMI, YUJI NAKATSUKASA
Publikováno v:
SIAM Journal on Scientific Computing; 2022, Vol. 44 Issue 5, pA3244-A3264, 21p
Autor:
Yuji Nakatsukasa, Alex Townsend
Publikováno v:
SIAM Journal on Numerical Analysis. 59:314-333
An important observation in compressed sensing is that the $\ell_0$ minimizer of an underdetermined linear system is equal to the $\ell_1$ minimizer when there exists a sparse solution vector and a certain restricted isometry property holds. Here, we
Publikováno v:
Linear Algebra and its Applications. 594:177-192
When a projection of a symmetric or Hermitian matrix to the positive semidefinite cone is computed approximately (or to working precision on a computer), a natural question is to quantify its accuracy. A straightforward bound invoking standard eigenv