Conditions for representation of a function of many arguments as the difference of convex functions
Igor Proudnikov
TL;DR
This paper establishes specific conditions under which a multivariable function can be expressed as the difference of two convex functions, aiding in optimization and analysis.
Contribution
It provides new necessary and sufficient conditions for representing multivariable functions as differences of convex functions.
Findings
Derived explicit conditions for convex difference representation
Applicable to multivariable functions in optimization
Enhances understanding of convex decomposition methods
Abstract
There are given conditions for represention of a function of many arguments as the difference of convex functions.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptimization and Variational Analysis · Advanced Optimization Algorithms Research · Aerospace Engineering and Control Systems