gptkbp:instanceOf
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gptkb:software
|
gptkbp:author
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gptkb:Stephen_Boyd
Steven Diamond
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gptkbp:category
|
gptkb:software
scientific computing
mathematical optimization
|
gptkbp:citation
|
Diamond, S., & Boyd, S. (2016). CVXPY: A Python-Embedded Modeling Language for Convex Optimization. Journal of Machine Learning Research, 17(83), 1-5.
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gptkbp:compatibleWith
|
gptkb:Pandas
gptkb:Jupyter_Notebook
gptkb:NumPy
gptkb:SciPy
|
gptkbp:describes
|
A Python-embedded modeling language for convex optimization problems.
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gptkbp:documentation
|
https://www.cvxpy.org/tutorial/index.html
|
gptkbp:firstReleased
|
2012
|
gptkbp:format
|
numerical solutions
Python expressions
|
https://www.w3.org/2000/01/rdf-schema#label
|
CVXPY
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gptkbp:latestReleaseVersion
|
1.4.2
|
gptkbp:license
|
gptkb:Apache_License_2.0
|
gptkbp:maintainedBy
|
cvxpy developers
|
gptkbp:npmPackage
|
gptkb:cvxpy
|
gptkbp:officialWebsite
|
https://www.cvxpy.org/
|
gptkbp:platform
|
cross-platform
|
gptkbp:programmingLanguage
|
gptkb:Python
|
gptkbp:repository
|
https://github.com/cvxpy/cvxpy
|
gptkbp:solvers
|
gptkb:CBC
gptkb:CPLEX
gptkb:SCS
gptkb:MOSEK
gptkb:XPRESS
gptkb:GLPK
GUROBI
ECOS
OSQP
|
gptkbp:status
|
active
|
gptkbp:supports
|
linear programming
convex optimization
quadratic programming
semidefinite programming
second-order cone programming
|
gptkbp:usedBy
|
gptkb:engineer
gptkb:researchers
students
|
gptkbp:usedFor
|
gptkb:machine_learning
gptkb:signal_processing
control systems
finance
operations research
statistics
engineering design
|
gptkbp:bfsParent
|
gptkb:Gurobi_Optimizer
|
gptkbp:bfsLayer
|
7
|