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.
Keywords for this software
References in zbMATH (referenced in 652 articles , 1 standard article )
Showing results 1 to 20 of 652.
Sorted by year (- Adriaens, Florian; De Bie, Tijl; Gionis, Aristides; Lijffijt, Jefrey; Matakos, Antonis; Rozenshtein, Polina: Relaxing the strong triadic closure problem for edge strength inference (2020)
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- Aliyev, Nicat; Mehrmann, Volker; Mengi, Emre: Approximation of stability radii for large-scale dissipative Hamiltonian systems (2020)
- Al-Matouq, Ali; Vincent, Tyrone: A convex optimization framework for the identification of homogeneous reaction systems (2020)
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- Budninskiy, Max; Abdelaziz, Ameera; Tong, Yiying; Desbrun, Mathieu: Laplacian-optimized diffusion for semi-supervised learning (2020)
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- Cen, Xiaoli; Xia, Yong; Gao, Runxuan; Yang, Tianzhi: On Chebyshev center of the intersection of two ellipsoids (2020)
- Chen, Ximing; Ogura, Masaki; Preciado, Victor M.: Bounds on the spectral radius of digraphs from subgraph counts (2020)
- Chun, Il Yong; Adcock, Ben: Uniform recovery from subgaussian multi-sensor measurements (2020)
- Chuong, Thai Doan: Semidefinite program duals for separable polynomial programs involving box constraints (2020)
- de Klerk, Etienne; Kuhn, Daniel; Postek, Krzysztof: Distributionally robust optimization with polynomial densities: theory, models and algorithms (2020)
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- Iwen, Mark A.; Preskitt, Brian; Saab, Rayan; Viswanathan, Aditya: Phase retrieval from local measurements: improved robustness via eigenvector-based angular synchronization (2020)
- Jiao, Liguo; Lee, Jae Hyoung; Zhou, Yuying: A hybrid approach for finding efficient solutions in vector optimization with SOS-convex polynomials (2020)
- Lim, Eunji: The limiting behavior of isotonic and convex regression estimators when the model is misspecified (2020)
- Maldonado, Sebastián; López, Julio; Vairetti, Carla: Profit-based churn prediction based on minimax probability machines (2020)