Works matching IS 00255610 AND DT 2019 AND VI 178 AND IP 1/2
Results: 15
Efficiency of minimizing compositions of convex functions and smooth maps.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 503, doi. 10.1007/s10107-018-1311-3
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Submodular optimization views on the random assignment problem.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 485, doi. 10.1007/s10107-018-1310-4
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A decomposition method for MINLPs with Lipschitz continuous nonlinearities.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 449, doi. 10.1007/s10107-018-1309-x
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On cutting planes for cardinality-constrained linear programs.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 417, doi. 10.1007/s10107-018-1306-0
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On the R-superlinear convergence of the KKT residuals generated by the augmented Lagrangian method for convex composite conic programming.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 381, doi. 10.1007/s10107-018-1300-6
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"Facet" separation with one linear program.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 361, doi. 10.1007/s10107-018-1299-8
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Oracle complexity of second-order methods for smooth convex optimization.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 327, doi. 10.1007/s10107-018-1293-1
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A general double-proximal gradient algorithm for d.c. programming.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 301, doi. 10.1007/s10107-018-1292-2
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Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 263, doi. 10.1007/s10107-018-1290-4
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Quadratic optimization with orthogonality constraint: explicit Łojasiewicz exponent and linear convergence of retraction-based line-search and stochastic variance-reduced gradient methods.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 215, doi. 10.1007/s10107-018-1285-1
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Generalized self-concordant functions: a recipe for Newton-type methods.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 145, doi. 10.1007/s10107-018-1282-4
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An inexact dual logarithmic barrier method for solving sparse semidefinite programs.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 109, doi. 10.1007/s10107-018-1281-5
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Sample average approximation with sparsity-inducing penalty for high-dimensional stochastic programming.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 69, doi. 10.1007/s10107-018-1278-0
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Optimization problems involving group sparsity terms.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 39, doi. 10.1007/s10107-018-1277-1
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Tight relaxations for polynomial optimization and Lagrange multiplier expressions.
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- Mathematical Programming, 2019, v. 178, n. 1/2, p. 1, doi. 10.1007/s10107-018-1276-2
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