Two numerical methods for optimizing matrix stability
By James V. Burke, A. S. Lewis, Michael L. Overton. 2002
110 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computational Theory and Mathematics, Numerical Analysis
View Paper: https://www.semanticscholar.org/paper/d5e6c903e27c9c0a7def5f264398b3d02dc600c5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- A. S. Lewis
- Michael L. Overton
- James V. Burke
- Peter Richtárik
- Xiaojun Chen
- Nicolas Loizou
- Martin Takác
- Rohollah Garmanjani
In Computational Theory and Mathematics
- A. S. Lewis
- Michael L. Overton
- James V. Burke
- Xiaojun Chen
- Daniel Petersson
- Rohollah Garmanjani
- Ali Emadi
- Sanjaka G. Wirasingha
In Numerical Analysis
- Michael L. Overton
- A. S. Lewis
- James V. Burke
- Xiaojun Chen
- Peter Richtárik
- Daniel Petersson
- Nicolas Loizou
- Francis R. Bach
Citations in the corpus
- Structured H∞‐control of infinite‐dimensional systems (2017, unknown): “Subgradients of α and α▷ are computed as in [42, 43].”
- A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization (2005, methodology): “This observation led us to consider a simple gradient sampling algorithm, first presented without any analysis in [BLO02b].”
- Spectral radius minimization for optimal average consensus and output feedback stabilization (2009, unknown): “Algorithm 1 (Gradient Bundle) proposed in Burke et al. (2002).”
- A Nonsmooth, Nonconvex Optimization Approach to Robust Stabilization by Static Output Feedback and Low-Order Controllers (2003, methodology): “However, we have devised a method based on gradient sampling that is very eective in practice and for which we have developed a local convergence theory ( Burke et al., 2002; Burke et al., 2003b).”