Mathematics of Operations Research
On the identification of active constraints
SIAM Journal on Numerical Analysis
Iterative linear programming solution of convex programs
Journal of Optimization Theory and Applications
Finite termination of the proximal point algorithm
Mathematical Programming: Series A and B
Weak sharp minima in mathematical programming
SIAM Journal on Control and Optimization
A Gauss-Newton method for convex composite optimization
Mathematical Programming: Series A and B
SIAM Journal on Matrix Analysis and Applications
Global Error Bounds for Convex Inequality Systems in Banach Spaces
SIAM Journal on Control and Optimization
New uniform parametric error bounds
Journal of Optimization Theory and Applications
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Hoffman's Error Bound, Local Controllability, and Sensitivity Analysis
SIAM Journal on Control and Optimization
Exact Penalization and Necessary Optimality Conditions for Generalized Bilevel Programming Problems
SIAM Journal on Optimization
Kantorovich's theorem on Newton's method in Riemannian Manifolds
Journal of Complexity
Projection algorithms and monotone operators
Projection algorithms and monotone operators
Metric Regularity and Constraint Qualifications for Convex Inequalities on Banach Spaces
SIAM Journal on Optimization
Error Bound Moduli for Conic Convex Systems on Banach Spaces
Mathematics of Operations Research
Singularities of Monotone Vector Fields and an Extragradient-type Algorithm
Journal of Global Optimization
Weak sharp minima revisited, part II: application to linear regularity and error bounds
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Trust-Region Methods on Riemannian Manifolds
Foundations of Computational Mathematics
Optimization Algorithms on Matrix Manifolds
Optimization Algorithms on Matrix Manifolds
Stable and Total Fenchel Duality for Convex Optimization Problems in Locally Convex Spaces
SIAM Journal on Optimization
Mathematical Programming: Series A and B - Series B - Special Issue: Well-posedness, stability and related topics
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This is the first paper dealing with the study of weak sharp minima for constrained optimization problems on Riemannian manifolds, which are important in many applications. We consider the notions of local weak sharp minima, boundedly weak sharp minima, and global weak sharp minima for such problems and establish their complete characterizations in the case of convex problems on finite-dimensional Riemannian manifolds and Hadamard manifolds. A number of the results obtained in this paper are also new for the case of conventional problems in finite-dimensional Euclidean spaces. Our methods involve appropriate tools of variational analysis and generalized differentiation on Riemannian and Hadamard manifolds developed and efficiently implemented in this paper.