Now showing items 11-14 of 14
Alternating Direction Augmented Lagrangian Methods for Semidefinite Programming
We present an alternating direction method based on an augmented Lagrangian framework for solving semidefinite programming (SDP) problems in standard form. At each iteration, the algorithm, also known as a two-splitting ...
Accelerating Convergence by Augmented Rayleigh-Ritz Projections For Large-Scale Eigenpair Computation
Iterative algorithms for large-scale eigenpair computation are mostly based subspace projections consisting of two main steps: a subspace update (SU) step that generates bases for approximate eigenspaces, followed by a ...
Augmented Lagrangian Alternating Direction Method for Matrix Separation Based on Low-Rank Factorization
The matrix separation problem aims to separate a low-rank matrix and a sparse matrix from their sum. This problem has recently attracted considerable research attention due to its wide range of potential applications. ...
Trace-Penalty Minimization for Large-scale Eigenspace Computation
The Rayleigh-Ritz (RR) procedure, including orthogonalization, constitutes a major bottleneck in computing relatively high-dimensional eigenspaces of large sparse matrices. Although operations involved in RR steps can be ...