CVX

CVX is a modeling system for constructing and solving disciplined convex programs (DCPs). CVX supports a number of standard problem types, including linear and quadratic programs (LPs/QPs), second-order cone programs (SOCPs), and semidefinite programs (SDPs). CVX can also solve much more complex convex optimization problems, including many involving nondifferentiable functions, such as ℓ1 norms. You can use CVX to conveniently formulate and solve constrained norm minimization, entropy maximization, determinant maximization, and many other convex programs. As of version 2.0, CVX also solves mixed integer disciplined convex programs (MIDCPs) as well, with an appropriate integer-capable solver.


References in zbMATH (referenced in 832 articles , 1 standard article )

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  1. Belyaeva, Anastasiya; Kubjas, Kaie; Sun, Lawrence J.; Uhler, Caroline: Identifying 3D genome organization in diploid organisms via Euclidean distance geometry (2022)
  2. Candogan, Utkan Onur; Chandrasekaran, Venkat: Convex graph invariant relaxations for graph edit distance (2022)
  3. Chen, Ye; Marković, Nikola; Ryzhov, Ilya O.; Schonfeld, Paul: Data-driven robust resource allocation with monotonic cost functions (2022)
  4. Dai, Tianyu; Sznaier, Mario: A convex optimization approach to synthesizing state feedback data-driven controllers for switched linear systems (2022)
  5. Doan, Xuan Vinh; Vavasis, Stephen: Low-rank matrix recovery with Ky Fan 2-(k)-norm (2022)
  6. Farjadnasab, Milad; Babazadeh, Maryam: Model-free LQR design by Q-function learning (2022)
  7. Gerami, Javad; Mozaffari, Mohammad Reza; Wanke, Peter F.; Correa, Henrique L.: Improving information reliability of non-radial value efficiency analysis: an additive slacks based measure approach (2022)
  8. Kanno, Yoshihiro: Structural reliability under uncertainty in moments: distributionally-robust reliability-based design optimization (2022)
  9. Karaki, Bilal J.; Mahmoud, Magdi S.: Scaled consensus for multiagent systems under denial-of-service attacks and exogenous disturbance (2022)
  10. Karbasy, Saeid Ansary; Salahi, Maziar: An efficient algorithm for the extended trust-region subproblem with two linear constraints (2022)
  11. Lee, Jon; Skipper, Daphne; Speakman, Emily: Gaining or losing perspective (2022)
  12. Lin, Yiding; Wang, Xiang; Zhang, Lei-Hong: Solving symmetric and positive definite second-order cone linear complementarity problem by a rational Krylov subspace method (2022)
  13. Molybog, Igor; Sojoudi, Somayeh; Lavaei, Javad: Role of sparsity and structure in the optimization landscape of non-convex matrix sensing (2022)
  14. Pillonetto, Gianluigi; Chiuso, Alessandro: Linear system identification using the sequential stabilizing spline algorithm (2022)
  15. Roig-Solvas, Biel; Sznaier, Mario: Euclidean distance bounds for linear matrix inequalities analytic centers using a novel bound on the Lambert function (2022)
  16. Sun, Yue; Qiu, Ruozhen; Sun, Minghe: Optimizing decisions for a dual-channel retailer with service level requirements and demand uncertainties: a Wasserstein metric-based distributionally robust optimization approach (2022)
  17. Yzenbrandt, Kai; Zhou, Julie: Minimax robust designs for regression models with heteroscedastic errors (2022)
  18. Zhang, Bo; Gao, YueLin; Liu, Xia; Huang, XiaoLi: An outcome-space-based branch-and-bound algorithm for a class of sum-of-fractions problems (2022)
  19. Zhang, Jingfan; Seiler, Peter; Carrasco, Joaquin: Zames-Falb multipliers for convergence rate: motivating example and convex searches (2022)
  20. Zhao, Bin; Geng, Pengbo; Chen, Wengu; Zeng, Zhu: Robust sparse recovery via a novel convex model (2022)

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