English

Directed Discrete Midpoint Convexity

Optimization and Control 2020-02-03 v1

Abstract

For continuous functions, midpoint convexity characterizes convex functions. By considering discrete versions of midpoint convexity, several types of discrete convexities of functions, including integral convexity, L^\natural-convexity and global/local discrete midpoint convexity, have been studied. We propose a new type of discrete midpoint convexity that lies between L^\natural-convexity and integral convexity and is independent of global/local discrete midpoint convexity. The new convexity, named DDM-convexity, has nice properties satisfied by L^\natural-convexity and global/local discrete midpoint convexity. DDM-convex functions are stable under scaling, satisfy the so-called parallelgram inequality and a proximity theorem with the same small proximity bound as that for L^{\natural}-convex functions. Several characterizations of DDM-convexity are given and algorithms for DDM-convex function minimization are developed. We also propose DDM-convexity in continuous variables and give proximity theorems on these functions.

Keywords

Cite

@article{arxiv.2001.11676,
  title  = {Directed Discrete Midpoint Convexity},
  author = {Akihisa Tamura and Kazuya Tsurumi},
  journal= {arXiv preprint arXiv:2001.11676},
  year   = {2020}
}

Comments

35 pages

R2 v1 2026-06-23T13:26:06.709Z