Regularized gradient-projection methods for finding the minimum-norm solution of the constrained convex minimization problem
Abstract Let H be a real Hilbert space and C be a nonempty closed convex subset of H. Assume that g is a real-valued convex function and the gradient ∇g is 1 L $\frac{1}{L}$ -ism with L > 0 $L>0$ . Let 0 < λ < 2 L + 2 $0<\lambda <\frac{2}{L+2}$ , 0 < β n < 1 $0<\beta_{n}&l...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2017-01-01
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| Series: | Journal of Inequalities and Applications |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13660-016-1289-4 |