Abstract
An important ingredient of our algorithms for solving QP and QCQP problems is the Euclidean projection on the convex set defined by separable convex constraints. To combine the gradient projection with the CG method effectively, it is necessary to have nontrivial bounds on the decrease of f along the projected-gradient path in terms of bounds on the spectrum of its Hessian matrix \({\mathsf {A}}\).
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Dostál, Z. (2016). Gradient Projection for Separable Convex Sets. In: Scalable Algorithms for Contact Problems. Advances in Mechanics and Mathematics, vol 36. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6834-3_6
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DOI: https://doi.org/10.1007/978-1-4939-6834-3_6
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