Pages that link to "Item:Q2943814"
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The following pages link to Benchmarking large-scale distributed convex quadratic programming algorithms (Q2943814):
Displaying 10 items.
- A parallel quadratic programming method for dynamic optimization problems (Q499159) (← links)
- Large-scale and distributed optimization. Contributions of the workshop, Lund, Sweden, June 14--16, 2017 (Q1667440) (← links)
- Network-decentralised optimisation and control: an explicit saturated solution (Q1737853) (← links)
- Dual fast projected gradient method for quadratic programming (Q1947612) (← links)
- A distributed algorithm for high-dimension convex quadratically constrained quadratic programs (Q2057223) (← links)
- A conjugate direction based simplicial decomposition framework for solving a specific class of dense convex quadratic programs (Q2301138) (← links)
- A secant-based Nesterov method for convex functions (Q2361131) (← links)
- An augmented Lagrangian based algorithm for distributed nonconvex optimization (Q2805706) (← links)
- Input–Output Performance of Linear–Quadratic Saddle-Point Algorithms With Application to Distributed Resource Allocation Problems (Q5125623) (← links)
- Hierarchical distributed optimization of constraint-coupled convex and mixed-integer programs using approximations of the dual function (Q6491323) (← links)
