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 411 articles , 1 standard article )

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  1. Arunachalam, Srinivasan; Molina, Abel; Russo, Vincent: Quantum hedging in two-round prover-verifier interactions (2018)
  2. Bakolas, E.: Constrained minimum variance control for discrete-time stochastic linear systems (2018)
  3. Bayraktar, Erhan; Wang, Gu: Quantile hedging in a semi-static market with model uncertainty (2018)
  4. Campi, Marco C.; Garatti, Simone: Wait-and-judge scenario optimization (2018)
  5. Candogan, Utkan Onur; Chandrasekaran, Venkat: Finding planted subgraphs with few eigenvalues using the Schur-Horn relaxation (2018)
  6. Cao, Lei; Woerdeman, Hugo J.: Real zero polynomials and A. Horn’s problem (2018)
  7. Deng, Zhibin; Fang, Shu-Cherng; Lu, Cheng; Guo, Xiaoling: A branch-and-cut algorithm using polar cuts for solving nonconvex quadratic programming problems (2018)
  8. Duarte, Belmiro P. M.; Wong, Weng Kee; Dette, Holger: Adaptive grid semidefinite programming for finding optimal designs (2018)
  9. Gillis, Nicolas; Sharma, Punit: A semi-analytical approach for the positive semidefinite Procrustes problem (2018)
  10. Halická, Margaréta; Trnovská, Mária: The Russell measure model: computational aspects, duality, and profit efficiency (2018)
  11. Hegde, Arun; Li, Wenyu; Oreluk, James; Packard, Andrew; Frenklach, Michael: Consistency analysis for massively inconsistent datasets in bound-to-bound data collaboration (2018)
  12. Johnson, Scott C.; Chakrabarty, Ankush; Hu, Jianghai; Żak, Stanisław H.; DeCarlo, Raymond A.: Dual-mode robust fault estimation for switched linear systems with state jumps (2018)
  13. Johnston, Nathaniel; Patterson, Everett: The inverse eigenvalue problem for entanglement witnesses (2018)
  14. Josz, Cédric; Molzahn, Daniel K.: Lasserre hierarchy for large scale polynomial optimization in real and complex variables (2018)
  15. Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J.Nathan; Brunton, Bingni W.; Brunton, Steven L.: Sparsity enabled cluster reduced-order models for control (2018)
  16. Kim, Donghwan; Fessler, Jeffrey A.: Another look at the fast iterative shrinkage/thresholding algorithm (FISTA) (2018)
  17. Kunis, Stefan; Reichenwallner, Benjamin; Reitzner, Matthias: Random approximation of convex bodies: monotonicity of the volumes of random tetrahedra (2018)
  18. Lee, Jae Hyoung; Jiao, Liguo: Solving fractional multicriteria optimization problems with sum of squares convex polynomial data (2018)
  19. Leermakers, Daan; Škorić, Boris: Optimal attacks on qubit-based quantum key recycling (2018)
  20. Miranda-Villatoro, Félix A.; Brogliato, Bernard; Castaños, Fernando: Set-valued sliding-mode control of uncertain linear systems: continuous and discrete-time analysis (2018)

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