The following pages link to V. Jeyakumar (Q425802):
Displaying 50 items.
- Asymptotic dual conditions characterizing optimality for infinite convex programs (Q1379971) (← links)
- Convex composite non-Lipschitz programming (Q1600101) (← links)
- An open mapping theorem using unbounded generalized Jacobians (Q1612598) (← links)
- Convergence of the Lasserre hierarchy of SDP relaxations for convex polynomial programs without compactness (Q1667169) (← links)
- Constraint qualifications for convex optimization without convexity of constraints: new connections and applications to best approximation (Q1681319) (← links)
- Characterizing best approximation from a convex set without convex representation (Q1717625) (← links)
- Convergent conic linear programming relaxations for cone convex polynomial programs (Q1728215) (← links)
- A convergent hierarchy of SDP relaxations for a class of hard robust global polynomial optimization problems (Q1728251) (← links)
- Convergent hierarchy of SDP relaxations for a class of semi-infinite convex polynomial programs and applications (Q1740163) (← links)
- Guaranteeing highly robust weakly efficient solutions for uncertain multi-objective convex programs (Q1754722) (← links)
- Generalized Lagrangian duality for nonconvex polynomial programs with polynomial multipliers (Q1756794) (← links)
- A bilevel Farkas lemma to characterizing global solutions of a class of bilevel polynomial programs (Q1785391) (← links)
- A general Farkas lemma and characterization of optimality for a nonsmooth program involving convex processes (Q1821698) (← links)
- On characterizing the solution sets of pseudolinear programs (Q1904699) (← links)
- Convex composite minimization with \(C^{1,1}\) functions (Q1905939) (← links)
- Robust best approximation with interpolation constraints under ellipsoidal uncertainty: strong duality and nonsmooth Newton methods (Q1937726) (← links)
- Exact SDP relaxations for classes of nonlinear semidefinite programming problems (Q1939707) (← links)
- Robust solutions of quadratic optimization over single quadratic constraint under interval uncertainty (Q1941033) (← links)
- Constraint qualifications characterizing Lagrangian duality in convex optimization (Q1956463) (← links)
- Exact conic programming reformulations of two-stage adjustable robust linear programs with new quadratic decision rules (Q1996732) (← links)
- A new bounded degree hierarchy with SOCP relaxations for global polynomial optimization and conic convex semi-algebraic programs (Q2010098) (← links)
- Generalized Farkas lemma with adjustable variables and two-stage robust linear programs (Q2025291) (← links)
- Calculating radius of robust feasibility of uncertain linear conic programs via semi-definite programs (Q2032008) (← links)
- Exact SDP reformulations of adjustable robust linear programs with box uncertainties under separable quadratic decision rules via SOS representations of non-negativity (Q2052413) (← links)
- Robust optimization and data classification for characterization of Huntington disease onset via duality methods (Q2139276) (← links)
- The radius of robust feasibility of uncertain mathematical programs: a survey and recent developments (Q2242324) (← links)
- Robust SOS-convex polynomial optimization problems: exact SDP relaxations (Q2257075) (← links)
- Characterizing robust solution sets of convex programs under data uncertainty (Q2260682) (← links)
- First and second order fractional programming duality (Q2265957) (← links)
- Convexifiability of continuous and discrete nonnegative quadratic programs for gap-free duality (Q2273897) (← links)
- A robust von Neumann minimax theorem for zero-sum games under bounded payoff uncertainty (Q2275574) (← links)
- A copositive Farkas lemma and minimally exact conic relaxations for robust quadratic optimization with binary and quadratic constraints (Q2294373) (← links)
- Strong duality for robust minimax fractional programming problems (Q2355075) (← links)
- Finding robust global optimal values of bilevel polynomial programs with uncertain linear constraints (Q2363578) (← links)
- An exact formula for radius of robust feasibility of uncertain linear programs (Q2401515) (← links)
- Sufficient global optimality conditions for non-convex quadratic minimization problems with box constraints (Q2433932) (← links)
- Global optimality principles for polynomial optimization over box or bivalent constraints by separable polynomial approximations (Q2442635) (← links)
- A dual criterion for maximal monotonicity of composition operators (Q2460925) (← links)
- Nonsmooth vector functions and continuous optimization (Q2464374) (← links)
- A note on strong duality in convex semidefinite optimization: necessary and sufficient conditions (Q2465563) (← links)
- Sufficient conditions for global optimality of bivalent nonconvex quadratic programs with inequality constraints (Q2471081) (← links)
- Necessary and sufficient constraint qualifications for solvability of systems of infinite convex inequalities (Q2474349) (← links)
- The strong conical hull intersection property for convex programming (Q2490330) (← links)
- Necessary and sufficient conditions for stable conjugate duality (Q2492483) (← links)
- Limiting \(\varepsilon\)-subgradient characterizations of constrained best approximation (Q2566244) (← links)
- A new geometric condition for Fenchel's duality in infinite dimensional spaces (Q2576721) (← links)
- Robust solutions to multi-objective linear programs with uncertain data (Q2630217) (← links)
- Kuhn-Tucker sufficiency for global minimum of multi-extremal mathematical programming problems (Q2642150) (← links)
- Sums of squares polynomial program reformulations for adjustable robust linear optimization problems with separable polynomial decision rules (Q2677664) (← links)
- Sums of squares characterizations of containment of convex semialgebraic sets (Q2789157) (← links)
