Works matching IS 00255610 AND DT 2016 AND VI 158 AND IP 1/2
Results: 20
Simple examples for the failure of Newton's method with line search for strictly convex minimization.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 23, doi. 10.1007/s10107-015-0913-2
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A polyhedral study of production ramping.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 175, doi. 10.1007/s10107-015-0919-9
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Sufficient optimality conditions hold for almost all nonlinear semidefinite programs.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 77, doi. 10.1007/s10107-015-0915-0
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Integrality gaps for strengthened linear relaxations of capacitated facility location.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 99, doi. 10.1007/s10107-015-0916-z
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Duality for mixed-integer convex minimization.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 547, doi. 10.1007/s10107-015-0917-y
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An efficient global algorithm for a class of indefinite separable quadratic programs.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 143, doi. 10.1007/s10107-015-0918-x
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Lipschitz and Hölder stability of optimization problems and generalized equations.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 35, doi. 10.1007/s10107-015-0914-1
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The submodular joint replenishment problem.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 207, doi. 10.1007/s10107-015-0920-3
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Exact quadratic convex reformulations of mixed-integer quadratically constrained problems.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 235, doi. 10.1007/s10107-015-0921-2
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Calmness modulus of fully perturbed linear programs.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 267, doi. 10.1007/s10107-015-0926-x
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Data-driven chance constrained stochastic program.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 291, doi. 10.1007/s10107-015-0929-7
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Sublinear time algorithms for approximate semidefinite programming.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 329, doi. 10.1007/s10107-015-0932-z
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A linear-time algorithm for trust region problems.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 363, doi. 10.1007/s10107-015-0933-y
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On Lipschitz optimization based on gray-box piecewise linearization.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 383, doi. 10.1007/s10107-015-0934-x
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Extended formulations for sparsity matroids.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 565, doi. 10.1007/s10107-015-0936-8
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Self-scaled bounds for atomic cone ranks: applications to nonnegative rank and cp-rank.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 417, doi. 10.1007/s10107-015-0937-7
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A smoothing SQP framework for a class of composite $$L_q$$ minimization over polyhedron.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 467, doi. 10.1007/s10107-015-0939-5
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A proximal method for composite minimization.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 501, doi. 10.1007/s10107-015-0943-9
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Fast projection onto the simplex and the $$\pmb {l}_\mathbf {1}$$ ball.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 575, doi. 10.1007/s10107-015-0946-6
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OSGA: a fast subgradient algorithm with optimal complexity.
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- Mathematical Programming, 2016, v. 158, n. 1/2, p. 1, doi. 10.1007/s10107-015-0911-4
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