Pages that link to "Item:Q907198"
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The following pages link to Stochastic algorithms for solving structured low-rank matrix approximation problems (Q907198):
Displaying 14 items.
- A quadratically convergent algorithm for structured low-rank approximation (Q285440) (← links)
- Iterative algorithms for large stochastic matrices (Q808164) (← links)
- Preface to the special issue NUMTA 2013 (Q907191) (← links)
- Stochastic dynamical low-rank approximation method (Q2000452) (← links)
- On the search of the shape parameter in radial basis functions using univariate global optimization methods (Q2022236) (← links)
- A gradient system approach for Hankel structured low-rank approximation (Q2029850) (← links)
- Structured low-rank approximation: optimization on matrix manifold approach (Q2114475) (← links)
- Blind deconvolution of covariance matrix inverses for autoregressive processes (Q2310396) (← links)
- Metaheuristic vs. deterministic global optimization algorithms: the univariate case (Q2422871) (← links)
- Optimization challenges in the structured low rank approximation problem (Q2434635) (← links)
- Weighted norms in subspace-based methods for time series analysis (Q2955991) (← links)
- On the Least-Squares Fitting of Data by Sinusoids (Q2958622) (← links)
- On Deterministic Diagonal Methods for Solving Global Optimization Problems with Lipschitz Gradients (Q5270520) (← links)
- (Q5400323) (← links)
