CVXPY: A Python-Embedded Modeling Language for Convex Optimization. CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at under the GPL license, along with documentation and examples

References in zbMATH (referenced in 14 articles , 1 standard article )

Showing results 1 to 14 of 14.
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  1. Diamond, S.; Takapoui, R.; Boyd, S.: A general system for heuristic minimization of convex functions over non-convex sets (2018)
  2. Anqi Fu, Balasubramanian Narasimhan, Stephen Boyd: CVXR: An R Package for Disciplined Convex Optimization (2017) arXiv
  3. Charisopoulos, Vasileios; Maragos, Petros: Morphological perceptrons: geometry and training algorithms (2017)
  4. Diamond, Steven; Boyd, Stephen: Stochastic matrix-free equilibration (2017)
  5. Hallac, David; Wong, Christopher; Diamond, Steven; Sharang, Abhijit; Sosič, Rok; Boyd, Stephen; Leskovec, Jure: SnapVX: a network-based convex optimization solver (2017)
  6. Kersting, Kristian; Mladenov, Martin; Tokmakov, Pavel: Relational linear programming (2017)
  7. Diamond, Steven; Boyd, Stephen: Matrix-free convex optimization modeling (2016)
  8. Diamond, Steven; Boyd, Stephen: CVXPY: a Python-embedded modeling language for convex optimization (2016)
  9. Lipp, Thomas; Boyd, Stephen: Variations and extension of the convex-concave procedure (2016)
  10. Miles Lubin, Emre Yamangil, Russell Bent, Juan Pablo Vielma: Polyhedral approximation in mixed-integer convex optimization (2016) arXiv
  11. O’Donoghue, Brendan; Chu, Eric; Parikh, Neal; Boyd, Stephen: Conic optimization via operator splitting and homogeneous self-dual embedding (2016)
  12. Vujanic, Robin; Goulart, Paul; Morari, Manfred: Robust optimization of schedules affected by uncertain events (2016)
  13. Xinyue Shen, Steven Diamond, Yuantao Gu, Stephen Boyd: Disciplined Convex-Concave Programming (2016) arXiv
  14. David Hallac, Christopher Wong, Steven Diamond, Abhijit Sharang, Rok Sosic, Stephen Boyd, Jure Leskovec: SnapVX: A Network-Based Convex Optimization Solver (2015) arXiv