diffopt jl

We have hosted the application diffopt jl in order to run this application in our online workstations with Wine or directly.

Quick description about diffopt jl:

DiffOpt.jl is a package for differentiating convex optimization programs (JuMP.jl or MathOptInterface.jl models) with respect to program parameters. Note that this package does not contain any solver. This package has two major backends, available via the reverse_differentiate! and forward_differentiate! methods, to differentiate models (quadratic or conic) with optimal solutions. Differentiable optimization is a promising field of convex optimization and has many potential applications in game theory, control theory and machine learning. Recent work has shown how to differentiate specific subclasses of convex optimization problems. But several applications remain unexplored. With the help of automatic differentiation, differentiable optimization can have a significant impact on creating end-to-end differentiable systems to model neural networks, stochastic processes, or a game.

Features:

• Documentation available
• Examples available
• Use with JuMP
• DiffOpt.jl is licensed under the MIT License
• DiffOpt currently supports linear, quadratic, and conic programs
• About Differentiating convex optimization programs

Programming Language: Julia.
Categories: