As long as your problem is convex, all these solvers work well. They all have their own API, but they all ask for the same information : values, first and second derivatives. Share

2024年10月10日 · convex-optimization; Share. Cite. Follow asked Oct 10, 2024 at 8:22. Jiro Jiro. 579 2 2 silver badges 10 ...

It's well known that linear least squares problems are convex optimization problems. Although this fact is stated in many texts explaining linear least squares I could not find any proof of it. That …

Optimization with convex constraints and convex objectives; notions related to convex optimization such as ...

2014年6月14日 · Convex optimization involves minimizing a convex objective function (or maximizing a concave objective function) over a convex set of constraints. Linear …

2012年2月17日 · Solver Foundation, a .Net runtime for mathematical programming, modeling, and optimization from Microsoft, probably provides what you want. They also have Optimization …

2024年10月7日 · I am writing a convex optimization problem with cvxpy, but it returns that the problem is not DPP even though it is. import cvxpy as cp import numpy as np from …

"For any convex optimization problem with differentiable objective and constraint function, any points that satisfy the KKT conditions are primal and dual optimal and have zero duality gap. …

A convex optimization problem consists of either minimizing a convex objective or maximizing a concave ...

2022年12月29日 · In a convex optimization problem, you can always solve for the KKT conditions (FONC) to achieve a set of minimizer candidates and be sure that all of them are your …