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 242 articles , 1 standard article )

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  1. Archibald, Rick; Gelb, Anne; Platte, Rodrigo B.: Image reconstruction from undersampled Fourier data using the polynomial annihilation transform (2016)
  2. Bai, Yanqin; Yan, Xin: Conic relaxations for semi-supervised support vector machines (2016)
  3. Bako, Laurent; Ohlsson, Henrik: Analysis of a nonsmooth optimization approach to robust estimation (2016)
  4. Baratchart, Laurent; Chevillard, Sylvain; Qian, Tao: Minimax principle and lower bounds in $H^2$-rational approximation (2016)
  5. Beck, Amir; Sabach, Shoham; Teboulle, Marc: An alternating semiproximal method for nonconvex regularized structured total least squares problems (2016)
  6. Bendory, Tamir; Dekel, Shai; Feuer, Arie: Robust recovery of stream of pulses using convex optimization (2016)
  7. Berta, Mario; Fawzi, Omar; Scholz, Volkher B.: Quantum bilinear optimization (2016)
  8. Bojarovska, Irena; Flinth, Axel: Phase retrieval from Gabor measurements (2016)
  9. Bunin, Gene A.: Extended reverse-convex programming: an approximate enumeration approach to global optimization (2016)
  10. Burger, Martin; Papafitsoros, Konstantinos; Papoutsellis, Evangelos; Schönlieb, Carola-Bibiane: Infimal convolution regularisation functionals of BV and $\mathrmL^p$ spaces. I: The finite $p$ case (2016)
  11. Chang, Chin-Yao; Zhang, Wei: Distributed control of inverter-based lossy microgrids for power sharing and frequency regulation under voltage constraints (2016)
  12. Chen, Peng; Wu, Lenan; Qi, Chenhao: Waveform optimization for target scattering coefficients estimation under detection and peak-to-average power ratio constraints in cognitive radar (2016)
  13. Das, Sonjoy; Chakravarty, Sourish: Predictive algorithm for detection of microcracks from macroscale observables (2016)
  14. Dey, Arnab; Patra, Sourav; Sen, Siddhartha: Absolute stability analysis for negative-imaginary systems (2016)
  15. Diamond, Steven; Boyd, Stephen: CVXPY: a python-embedded modeling language for convex optimization (2016)
  16. Doan, Xuan Vinh; Vavasis, Stephen: Finding the largest low-rank clusters with Ky Fan $2$-$k$-norm and $\ell_1$-norm (2016)
  17. Dumitrescu, Bogdan; Şicleru, Bogdan C.; Avram, Florin: Modeling probability densities with sums of exponentials via polynomial approximation (2016)
  18. Fornasier, Massimo; Hütter, Jan-Christian: Consistency of probability measure quantization by means of power repulsion-attraction potentials (2016)
  19. Fu, Rui; Gutfraind, Alexander; Brandeau, Margaret L.: Modeling a dynamic bi-layer contact network of injection drug users and the spread of blood-borne infections (2016)
  20. Giryes, Raja: Sampling in the analysis transform domain (2016)

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