CVXOPT; Python Software for Convex Optimization. CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language.

References in zbMATH (referenced in 20 articles )

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  1. Diamond, Steven; Boyd, Stephen: CVXPY: a python-embedded modeling language for convex optimization (2016)
  2. Shakeri, Heman; Poggi-Corradini, Pietro; Scoglio, Caterina; Albin, Nathan: Generalized network measures based on modulus of families of walks (2016)
  3. Van Cleve, Jeremy: Cooperation, conformity, and the coevolutionary problem of trait associations (2016)
  4. Bogolubsky, L.I.; Raigorodskii, A.M.: On the measurable chromatic number of a space of dimension $n \leq 24$ (2015)
  5. Bonettini, S.; Chiuso, A.; Prato, M.: A scaled gradient projection method for Bayesian learning in dynamical systems (2015)
  6. Li, Li: Selected applications of convex optimization (2015)
  7. Birch, Elsa W.; Udell, Madeleine; Covert, Markus W.: Incorporation of flexible objectives and time-linked simulation with flux balance analysis (2014)
  8. Doran, Gary; Ray, Soumya: A theoretical and empirical analysis of support vector machine methods for multiple-instance classification (2014)
  9. Müller, Andreas C.; Behnke, Sven: Pystruct-learning structured prediction in Python (2014)
  10. Xanthopoulos, Petros; Guarracino, Mario R.; Pardalos, Panos M.: Robust generalized eigenvalue classifier with ellipsoidal uncertainty (2014)
  11. Ermon, Stefano; Xue, Yexiang; Gomes, Carla; Selman, Bart: Learning policies for battery usage optimization in electric vehicles (2013)
  12. Chiu, Edmond Kwan-Yu; Wang, Qiqi; Hu, Rui; Jameson, Antony: A conservative mesh-free scheme and generalized framework for conservation laws (2012)
  13. Mattingley, Jacob; Boyd, Stephen: CVXGEN: a code generator for embedded convex optimization (2012)
  14. Ruotsalainen, Lauri; Vuorinen, Matti: Numerical methods with Sage (2012)
  15. Andersen, Martin S.; Dahl, Joachim; Vandenberghe, Lieven: Implementation of nonsymmetric interior-point methods for linear optimization over sparse matrix cones (2010)
  16. Auslender, Alfred; Shefi, Ron; Teboulle, Marc: A moving balls approximation method for a class of smooth constrained minimization problems (2010)
  17. Buriol, Luciana S.; Hirsch, Michael J.; Pardalos, Panos M.; Querido, Tania; Resende, Mauricio G.C.; Ritt, Marcus: A biased random-key genetic algorithm for road congestion minimization (2010)
  18. Liu, Zhang; Vandenberghe, Lieven: Interior-point method for nuclear norm approximation with application to system identification (2010)
  19. Dahl, Joachim; Vandenberghe, Lieven; Roychowdhury, Vwani: Covariance selection for nonchordal graphs via chordal embedding (2008)
  20. Durocher, Stephane; Kranakis, Evangelos; Krizanc, Danny; Narayanan, Lata: Balancing traffic load using one-turn rectilinear routing (2008)