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Tensorial Convex Functional and Applications
Implicit Functions and Regular Points in Quasidifferentiable
Comparisons of Two Types
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Advances in Optimization: Proceedings of the 6th French-German Colloquium on ...
Werner Oettli,Diethard Pallaschke
No preview available - 2014
analysis apply approximation AR(D assume assumptions Banach spaces bang-bang bounded closed convex compact compute cone consider constraints convergence space Convex Analysis convex function convex optimization convex set Corollary defined definition denote differentiable functions dimensional directional derivative duality equation equivalent Example exists formula function f funotion Gateaux differentiability given Hence Hilbert space holds implies iteration Lagrange multiplier Lemma linear Lipschitz Lipschitz continuous Lipschitzian lower semi-continuous mapping Math matrix maximal monotone method of partial minimizer monotone operator Moreover nonempty nonlinear programming nonsmooth norm obtain optimal control optimality conditions optimization problems pair parameter partial inverses perturbed Proof properties Proposition 2.2 quadratic quasidifferentiable relation Remark Rockafellar saddle point satisfied second order second-order sequence SIAM SIP(t stability subdifferential subgradient subset sufficient conditions Suppose Theorem theory topological space topology variational inequalities vector