Výsledky vyhledávání - 90C25 Mathematical Programming - convex programming

  1. 1

    On semidefinite programming relaxations for a class of robust SOS-convex polynomial optimization problems Autor Sun, Xiangkai, Huang, Jiayi, Teo, Kok Lay

    ISSN: 0925-5001, 1573-2916
    Vydáno: New York Springer US 01.03.2024
    Vydáno v Journal of global optimization (01.03.2024)
    “…In this paper, we deal with a new class of SOS-convex (sum of squares convex) polynomial optimization problems with spectrahedral uncertainty data in both the objective and constraints…”
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  2. 2

    Shapes and recession cones in mixed-integer convex representability Autor Zadik, Ilias, Lubin, Miles, Vielma, Juan Pablo

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024
    Vydáno v Mathematical programming (01.03.2024)
    “…Mixed-integer convex representable (MICP-R) sets are those sets that can be represented exactly through a mixed-integer convex programming formulation…”
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  3. 3

    Data-driven inverse optimization with imperfect information Autor Mohajerin Esfahani, Peyman, Shafieezadeh-Abadeh, Soroosh, Hanasusanto, Grani A., Kuhn, Daniel

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2018
    Vydáno v Mathematical programming (01.01.2018)
    “…In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an…”
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  4. 4

    Convex hull results on quadratic programs with non-intersecting constraints Autor Joyce, Alexander, Yang, Boshi

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2024
    Vydáno v Mathematical programming (01.05.2024)
    “…Let F ⊆ R n be a nonempty closed set. Understanding the structure of the closed convex hull C ¯ ( F ) : = conv ¯ { ( x , x x T ) | x ∈ F…”
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  5. 5

    A slightly lifted convex relaxation for nonconvex quadratic programming with ball constraints Autor Burer, Samuel

    ISSN: 0025-5610, 1436-4646
    Vydáno: Heidelberg Springer Nature B.V 01.05.2025
    Vydáno v Mathematical programming (01.05.2025)
    “… However, there is no known explicit, tractable, exact convex representation for m≥3. In this paper, we construct a new, polynomially sized semidefinite relaxation for all m, which does not employ a disjunctive approach…”
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  6. 6

    A Benson-type algorithm for bounded convex vector optimization problems with vertex selection Autor Dörfler, Daniel, Löhne, Andreas, Schneider, Christopher, Weißing, Benjamin

    ISSN: 1055-6788, 1029-4937
    Vydáno: Abingdon Taylor & Francis 04.05.2022
    Vydáno v Optimization methods & software (04.05.2022)
    “…We present an algorithm for approximately solving bounded convex vector optimization problems…”
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  7. 7

    New analysis and results for the Frank–Wolfe method Autor Freund, Robert M., Grigas, Paul

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2016
    Vydáno v Mathematical programming (01.01.2016)
    “…We present new results for the Frank–Wolfe method (also known as the conditional gradient method). We derive computational guarantees for arbitrary step-size…”
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  8. 8

    Complexity of first-order inexact Lagrangian and penalty methods for conic convex programming Autor Necoara, I., Patrascu, A., Glineur, F.

    ISSN: 1055-6788, 1029-4937
    Vydáno: Abingdon Taylor & Francis 04.03.2019
    Vydáno v Optimization methods & software (04.03.2019)
    “…In this paper we present a complete iteration complexity analysis of inexact first-order Lagrangian and penalty methods for solving cone-constrained convex problems that have or…”
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  9. 9

    NP-hardness of deciding convexity of quartic polynomials and related problems Autor Ahmadi, Amir Ali, Olshevsky, Alex, Parrilo, Pablo A., Tsitsiklis, John N.

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer-Verlag 01.02.2013
    Vydáno v Mathematical programming (01.02.2013)
    “…) is globally convex. This solves a problem that has been open since 1992 when N. Z. Shor asked for the complexity of deciding convexity for quartic polynomials…”
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  10. 10

    Copositivity and constrained fractional quadratic problems Autor Amaral, Paula, Bomze, Immanuel M., Júdice, Joaquim

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2014
    Vydáno v Mathematical programming (01.08.2014)
    “…) and Standard Fractional Quadratic Problem (StFQP). Based on these formulations, Semidefinite Programming relaxations are derived for finding good lower bounds…”
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  11. 11

    Semiglobal exponential stability of the discrete-time Arrow-Hurwicz-Uzawa primal-dual algorithm for constrained optimization Autor Bin, Michelangelo, Notarnicola, Ivano, Parisini, Thomas

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2024
    Vydáno v Mathematical programming (01.11.2024)
    “…We consider the discrete-time Arrow-Hurwicz-Uzawa primal-dual algorithm, also known as the first-order Lagrangian method, for constrained optimization problems involving a smooth strongly convex cost…”
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  12. 12

    A unified approach to error bounds for structured convex optimization problems Autor Zhou, Zirui, So, Anthony Man-Cho

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2017
    Vydáno v Mathematical programming (01.10.2017)
    “… convex optimization problems, in which the objective function is the sum of a smooth convex function…”
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  13. 13

    Branch-and-bound performance estimation programming: a unified methodology for constructing optimal optimization methods Autor Das Gupta, Shuvomoy, Van Parys, Bart P. G., Ryu, Ernest K.

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024
    Vydáno v Mathematical programming (01.03.2024)
    “…We present the Branch-and-Bound Performance Estimation Programming (BnB-PEP), a unified methodology for constructing optimal first-order methods for convex and nonconvex optimization…”
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  14. 14

    Mathematical programming with Semilocally Subconvex functions over cones Autor Sharma, Vani, Chaudhary, Mamta, Grover, Meetu Bhatia

    ISSN: 2311-004X, 2310-5070
    Vydáno: 02.09.2025
    “… Then we investigate the optimalsolutions of the mathematical programming problem (MP) over cones using these functions, directional derivatives, andthe alternative theorem…”
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  15. 15

    Two Convergent Primal–Dual Hybrid Gradient Type Methods for Convex Programming with Linear Constraints Autor Sun, Min, Liu, Jing, Tian, Maoying

    ISSN: 1017-060X, 1735-8515
    Vydáno: Singapore Springer Nature Singapore 01.06.2023
    “…As an effective tool for convex programming, the primal–dual hybrid gradient (PDHG) method has been widely applied in science and engineering computing field…”
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  16. 16

    On the convex hull of convex quadratic optimization problems with indicators Autor Wei, Linchuan, Atamtürk, Alper, Gómez, Andrés, Küçükyavuz, Simge

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024
    Vydáno v Mathematical programming (01.03.2024)
    “…We consider the convex quadratic optimization problem in R n with indicator variables and arbitrary constraints on the indicators…”
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  17. 17

    Randomized Methods for Computing Optimal Transport Without Regularization and Their Convergence Analysis Autor Xie, Yue, Wang, Zhongjian, Zhang, Zhiwen

    ISSN: 0885-7474, 1573-7691
    Vydáno: New York Springer US 01.08.2024
    Vydáno v Journal of scientific computing (01.08.2024)
    “…The optimal transport (OT) problem can be reduced to a linear programming (LP) problem through discretization…”
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  18. 18

    FISTA is an automatic geometrically optimized algorithm for strongly convex functions Autor Aujol, J.-F., Dossal, Ch, Rondepierre, A.

    ISSN: 0025-5610, 1436-4646
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024
    Vydáno v Mathematical programming (01.03.2024)
    “…In this work, we are interested in the famous FISTA algorithm. We show that FISTA is an automatic geometrically optimized algorithm for functions satisfying a…”
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  19. 19

    Convex optimization via inertial algorithms with vanishing Tikhonov regularization: fast convergence to the minimum norm solution Autor Attouch, Hedy, László, Szilárd Csaba

    ISSN: 1432-2994, 1432-5217
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024
    “…In a Hilbertian framework, for the minimization of a general convex differentiable function f , we introduce new inertial dynamics and algorithms that generate trajectories and iterates that converge…”
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  20. 20

    Differential stability of convex optimization problems under weaker conditions Autor An, Duong Thi Viet, Köbis, Markus A., Tuyen, Nguyen Van

    ISSN: 0233-1934, 1029-4945
    Vydáno: Philadelphia Taylor & Francis 01.02.2020
    Vydáno v Optimization (01.02.2020)
    “…Differential stability properties of convex optimization problems in Hausdorff locally convex topological vector spaces are considered in this paper…”
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