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Recently, L1-norm-based discriminant subspace learning has attracted much more attention in dimensionality reduction and machine learning. However, most existing approaches solve the column vectors of the optimal projection matrix one by one with greedy strategy. Thus, the obtained optimal projection matrix does not necessarily best optimize the corresponding trace ratio objective function, which...
An improved iterative algorithm is presented in this paper for solving finite difference approximation to elliptic equations. This algorithm is based on fourth order finite difference scheme and has obvious property of parallelism. The convergence theory is discussed in detail. Numerical experiments show that the new algorithm has faster convergence rate and higher accuracy than Jacobi method, the...
In this paper, an adaptive full multigrid method is presented for the iterative solution of the large scale sparse linear systems resulting from the finite difference discretization of two dimensional Poisson equation. This method is based on a hybrid Gauss-Seidel iterative algorithm, which is build by a modified stencil elimination procedure. Numerical experiments are conducted to show the feasibility...
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