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CVXPY: A Python-Embedded Modeling Language for Convex Optimization.

Steven Diamond1, Stephen Boyd1

  • 1Departments of Computer Science and Electrical Engineering, Stanford University, Stanford, CA 94305, USA.

Journal of Machine Learning Research : JMLR
|July 5, 2016
PubMed
Summary
This summary is machine-generated.

CVXPY is a Python-based language simplifying convex optimization problems. It offers a natural syntax, integrating seamlessly with Python features for easier problem-solving.

Keywords:
Pythonconic programmingconvex optimizationconvexity verificationdomain-specific languages

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Area of Science:

  • Computational Mathematics
  • Computer Science

Background:

  • Convex optimization problems traditionally require restrictive standard forms for solvers.
  • Integrating optimization with general-purpose programming languages can be challenging.

Purpose of the Study:

  • Introduce CVXPY, a domain-specific language for convex optimization in Python.
  • Enable users to express optimization problems naturally, leveraging Python's features.

Main Methods:

  • CVXPY embeds a domain-specific language within Python.
  • It translates natural mathematical expressions into standard forms for solvers.
  • Facilitates integration with Python's object-oriented design and parallelism.

Main Results:

  • CVXPY provides an intuitive syntax for defining convex optimization problems.
  • It simplifies the process of combining optimization with Python's high-level functionalities.
  • The library is readily available with comprehensive documentation and examples.

Conclusions:

  • CVXPY democratizes convex optimization by offering a user-friendly Python interface.
  • It enhances productivity for researchers and developers working with optimization problems.