COMPUTING THE NEAREST BISYMMETRIC POSITIVE SEMIDEFINITE MATRIX UNDER THE SPECTRAL RESTRICTION 双对称半正定矩阵特征值矩阵范数数值计算光谱限制Let A and C denote real n × n matrices. Given real n-vectors x1,……… ,xm,m≤n,and a set of numbers (L)={λ1,λ2…λm},We descrbe(Ⅰ)the set...
1) symmetric positive semidefinite 对称半正定 1. The left and right inverse eigenvalue problem for symmetric positive definite and symmetric positive semidefinite matrices on subspace; 子空间上的对称正定及对称半正定阵的左右特征值反问题 更多例句>> 2) symmetric positive semidefinite solution 对称半...
Martin Slawski, Ping Li, and Matthias Hein. Regularization-free estimation in trace regression with symmetric positive semidefinite matrices. In NIPS, 2015.Slawski, M., Li, P. & Hein, M. (2015) Regularization-free estimation in trace regression with symmetric positive semidefinite matrices. ...
LEAST—SQUARES SOLUTION OF AXB=D OVER SYMMETRIC POSITIVE SEMIDEFINITE MATRICES X Least-squares solution of AXB=D with respect to symmetric positive semidefinite matrix X is considered.By making use of the generalized singular value ecom... AnpingLiao ZhongzhiBai - 《Journal of Computational Mathematics...
Regularization-free estimation in trace regression with symmetric positive semidefinite matrices 来自 arXiv.org 喜欢 0 阅读量: 35 作者:M Slawski,P Li,M Hein 摘要: Over the past few years, trace regression models have received considerable attention in the context of matrix completion, quantum ...
A symmetric positive definite matrix A(3) of order n– 2 is obtained, which can in turn be factorized. The procedure is repeated until a matrix A(n) of order 1, a number, is obtained. All the matrices of the sequence A(1)≡ A, A(2),…, A(n) are symmetric positive definite, ...
In the convergence theory of multisplittings for symmetric positive definite (s.p.d.) matrices it is usually assumed that the weighting matrices are scalar matrices, i.e., multiples of the identity. In this paper, this restrictive condition is eliminated. In its place it is assumed that more...
An n× n real symmetric matrix A is said to be positive definite if, given any real vector x≠ 0, then xTAx>0. Note that xTAx is a 1 × 1 matrix. Positive definite matrices occur in a variety of problems, for example least squares approximation calculations (see Problem 9.39). We ...
After that, we extend many properties of positive semidefinite matrices to the case of third-order symmetric tensors. In particular, analogue to the widely used semidefinite programming (SDP for short), we introduce the semidefinite programming over the space of third-order symmetric tensors (T-...
Higher-Order Duality for Minimax Fractional Type Programming Involving Symmetric MatricesHigher-Order (Fαφ )β Vector-Pseudoquasi-Type IHigher-Order DualityMinimax Fractional Type ProgrammingPositive Semidefinite Symmetric MatrixConvexity and generalized convexity play important roles in optimization theory. ...