Mixture Augmented Lagrange Multiplier Method for Tensor Recovery and Its Applications

The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices

This paper proposes scalable and fast algorithms for solving the Robust PCA problem, namely recovering a low-rank matrix with an unknown fraction of its entries being arbitrarily corrupted. This problem arises in many applications, such as image processing, web data ranking, and bioinformatic data analysis. It was recently shown that under surprisingly broad conditions, the Robust PCA problem c...

The Lagrange Multiplier Method for Dirichlet's Problem

The Lagrange multiplier method of Babuska for the approximate solution of Dirichlet's problem for second order elliptic equations is reformulated. Based on this formulation, new estimates for the error in the solution and the boundary flux are given. Efficient methods for the solution of the approximate problem are discussed.

The Trifocal Tensor and Its Applications in Augmented Reality

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Multiple Lagrange Multiplier Method for Constrained Evolutionary Optimization

One of the well-known problems in evolutionary search for solving optimization problem is the premature convergence. The general constrained optimization techniques such as hybrid evolutionary programming, two{phase evolutionary programming, and Evolian algorithms are not safe from the same problem in the rst phase. To overcome this problem, we apply the sharing function to the Evolian algorith...

A Lagrange Multiplier Method for Certain Constrained Min-Max Problems