Convex optimization in julia

jl, a convex optimization modeling framework in Julia. Convex. jl translates problems from a user-friendly functional language into an abstract syntax tree describing the problem. This concise representation of the global structure of the problem allows Convex.

What solvers does convex support?

Convex jl supports many solvers, including COSMO, Mosek, Gurobi, ECOS, SCS and GLPK, through MathOptInterface Note that Convex jl was previously called CVX jl

This package is under active development; we welcome bug reports and feature requests

For usage questions, please contact us via the Julia Discourse


Categories

Convex optimization in svm
Convex analysis
Convex analysis and optimization
Beyond convexity
Is convex concave up or down
Slope of convex curve
Difference between concave and convex curve
Difference between concave and convex slope
Convex optimization in ai
Convex optimization negative definite
What is non convex optimization
Convex optimization of functions
Opposite of optimizing
Convex optimization permutation
Convex optimization for electrical engineering
Convex optimization
Convex optimization by stephen boyd and lieven vandenberghe
Bandit convex optimization towards tight bounds
Optimization under constraints
Convex optimization and applications