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Non-consistent approximations of self-adjoint eigenproblems: Application to the supercell method
Non-consistent approximations self-adjoint eigenproblems Functional Analysis
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2012/5/24
In this article, we introduce a general theoretical framework to analyze non-consistent approximations of the discrete eigenmodes of a self-adjoint operator. We focus in particular on the discrete eig...
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Inverse Power Method for Nonlinear Eigenproblems Applications 1-Spectral Clustering Sparse PCA
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2011/3/2
Many problems in machine learning and statistics can be formulated as (generalized)eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding crit...
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Inverse Power Method Nonlinear Eigenproblems
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2011/1/4
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding cri...
Minimizing Communication for Eigenproblems and the Singular Value Decomposition
Minimizing Communication Eigenproblems the Singular Value Decomposition
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2010/11/19
Algorithms have two costs: arithmetic and communication. The latter represents the cost of moving data, either between levels of a memory hierarchy, or between processors over a network. Communicatio...
A new computational harmonic projection algorithm for large unsymmetric generalized eigenproblems
Eigenvalue unsymmetric matrix harmonic Arnoldi
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2010/9/13
The harmonic projection method can be used to find interior eigenpairs of large matrices. Given a target point or shift σ to which the needed interior eigenvalues are close, the desired interior eigen...