Linear discriminant analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition. However, an intrinsic limitation of LDA is the sensitivity to the presence of outliers, due to using the Frobenius norm to measure the inter-class and intra-class distances. In this paper, we propose a novel rotationa...

A new lower bound on minimal singular values of real matrices based on Frobenius norm and determinant is presented. We show that under certain assumptions on matrix A is this estimate sharper than a recent bound from Hong and Pan based on a matrix norm and determinant.

in this paper‎, ‎we study convergence behavior of the global fom (gl-fom) and global gmres (gl-gmres) methods for solving the matrix equation $axb=c$ where $a$ and $b$ are symmetric positive definite (spd)‎. ‎we present some new theoretical results of these methods such as computable exact expressions and upper bounds for the norm of the error and residual‎. ‎in particular‎, ‎the obtained upper...

In the present paper, we give some new convergence results of the global GMRES method for multiple linear systems. In the case where the coefficient matrix A is diagonalizable, we derive new upper bounds for the Frobenius norm of the residual. We also consider the case of normal matrices and we propose new expressions for the norm of the residual. AMS subject classification: 65F10.

We present a new lower bound on minimal singular values of real matrices base on Frobenius norm and determinant. We show, that under certain assumptions on matrix A is our estimate sharper than two recent ones based on a matrix norm and determinant.

in the present paper‎, ‎we propose an iterative algorithm for‎ ‎solving the generalized $(p,q)$-reflexive solution of the quaternion matrix‎ ‎equation $overset{u}{underset{l=1}{sum}}a_{l}xb_{l}+overset{v} ‎{underset{s=1}{sum}}c_{s}widetilde{x}d_{s}=f$‎. ‎by this iterative algorithm‎, ‎the solvability of the problem can be determined automatically‎. ‎when the‎ ‎matrix equation is consistent over...

For two n × complex matrices A and B , we define the q -deformed commutator as [ ] : = − for a real parameter . In this paper, investigate generalization of Böttcher-Wenzel inequality which gives sharp upper bound (Frobenius) norm commutator. our generalisation, bounds on This can be studied in different scenarios: firstly general matrices, secondly traceless matrices. both scenarios, partial a...

This paper studies matrix completion under a general sampling model using the max-norm as a convex relaxation for the rank of the matrix. The optimal rate of convergence is established for the Frobenius norm loss. It is shown that the max-norm constrained minimization method is rate-optimal and it yields a more stable approximate recovery guarantee, with respect to the sampling distributions, t...