Hybrid proximal linearized algorithm for the split DC program in infinite-dimensional real Hilbert spaces
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Publication:824790
DOI10.1186/s13660-018-1840-6zbMath1498.90164OpenAlexW2889936000WikidataQ58706012 ScholiaQ58706012MaRDI QIDQ824790
Pei-Jung Yang, Chih-Sheng Chuang
Publication date: 15 December 2021
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13660-018-1840-6
Nonconvex programming, global optimization (90C26) Optimality conditions and duality in mathematical programming (90C46) Programming in abstract spaces (90C48) Semi-infinite programming (90C34)
Cites Work
- Global convergence of a proximal linearized algorithm for difference of convex functions
- Lagrange-type duality in DC programming
- Local and global optimality conditions for dc infinite optimization problems
- Totally convex functions for fixed points computation and infinite dimensional optimization
- Convergence of generalized proximal point algorithms
- The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
- Optimality conditions for DC programming problems with reverse convex constraints
- Lagrange duality in canonical DC programming
- Extended Farkas lemma and strong duality for composite optimization problems with DC functions
- Stable and Total Fenchel Duality for DC Optimization Problems in Locally Convex Spaces
- Two simple relaxed perturbed extragradient methods for solving variational inequalities in Euclidean spaces
- FIXED-POINT THEOREMS FOR NONCOMPACT MAPPINGS IN HILBERT SPACE
- Convex analysis and monotone operator theory in Hilbert spaces
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