Novel convex decomposition of piecewise affine functions
Not on the map. Why?
Abstract (arXiv)
In this paper, we present a novel approach to decompose a given piecewise affine (PWA) function into two convex PWA functions. Convex decompositions are useful to speed up or distribute evaluations of PWA functions. Different approaches to construct a convex decomposition have already been published. However, either the two resulting convex functions have very high or very different complexities, which is often undesirable, or the decomposition procedure is inapplicable even for simple cases. Our novel methodology significantly reduces these drawbacks in order to extend the applicability of convex decompositions.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Aug 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 2; 2025: 0; 2026: 1.
4 papers.
- 2024The Real Tropical Geometry of Neural Networkscited by 23
- 2024Decomposition Polyhedra of Piecewise Linear Functionscited by 9
- 2023Representing Piecewise Linear Functions by Functions with Small Aritycited by 7
- 2026Hidden Monotonicity: Explaining Deep Neural Networks via their DC Decompositioncited by 0
- 2026Hidden Monotonicity: Explaining Deep Neural Networks via their DC Decomposition12 Jan 2026
- 2024Decomposition Polyhedra of Piecewise Linear Functions7 Oct 2024
- 2024The Real Tropical Geometry of Neural Networks18 Mar 2024
- 2023Representing Piecewise Linear Functions by Functions with Small Arity26 May 2023