Strong Log-Concavity Does Not Imply Log-Submodularity
Alkis Gotovos

TL;DR
This paper disproves a conjecture by showing that strong log-concavity of discrete distributions does not necessarily imply log-submodularity, challenging assumptions about their relationship.
Contribution
It provides a counterexample demonstrating that strong log-concavity does not imply log-submodularity in discrete distributions.
Findings
Counterexample disproves the conjecture
Challenges previous assumptions about distribution properties
Clarifies the relationship between log-concavity and log-submodularity
Abstract
We disprove a recent conjecture regarding discrete distributions and their generating polynomials stating that strong log-concavity implies log-submodularity.
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Markov Chains and Monte Carlo Methods · Matrix Theory and Algorithms
