Pages that link to "Item:Q1625764"
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The following pages link to A descent hybrid conjugate gradient method based on the memoryless BFGS update (Q1625764):
Displaying 16 items.
- Improved conjugate gradient method for nonlinear system of equations (Q2027665) (← links)
- A new descent spectral Polak-Ribière-Polyak method based on the memoryless BFGS update (Q2052328) (← links)
- Diagonally scaled memoryless quasi-Newton methods with application to compressed sensing (Q2083385) (← links)
- Nonmonotone diagonally scaled limited-memory BFGS methods with application to compressive sensing based on a penalty model (Q2165892) (← links)
- A hybrid quasi-Newton method with application in sparse recovery (Q2167383) (← links)
- An efficient hybrid conjugate gradient method with sufficient descent property for unconstrained optimization (Q5058391) (← links)
- A globally convergent gradient-like method based on the Armijo line search (Q5080090) (← links)
- A modified conjugate gradient parameter via hybridization approach for solving large-scale systems of nonlinear equations (Q6055844) (← links)
- (Q6097284) (← links)
- A three-term conjugate gradient method with a random parameter for large-scale unconstrained optimization and its application in regression model (Q6137748) (← links)
- A new hybrid conjugate gradient algorithm based on the Newton direction to solve unconstrained optimization problems (Q6138360) (← links)
- (Q6191840) (← links)
- A new self-scaling memoryless quasi-Newton update for unconstrained optimization (Q6564739) (← links)
- Hypergraph-based convex semi-supervised unconstraint symmetric matrix factorization for image clustering (Q6595309) (← links)
- A family of limited memory three term conjugate gradient methods (Q6661110) (← links)
- Two efficient spectral hybrid CG methods based on memoryless BFGS direction and Dai–Liao conjugacy condition (Q6661117) (← links)
