Submodular Function Minimization with Dueling Oracle

ICLR 2026 Conference Submission25553 Authors

Keywords: submodular minimization, deling oracle, preference-based optimization

TL;DR: We study submodular minimization with a dueling oracle giving noisy pairwise feedback.

Abstract: We consider submodular function minimization using a \textit{dueling oracle}, a noisy pairwise comparison oracle that provides relative feedback on function values between two queried sets. The oracle's responses are governed by a \textit{transfer function}, which characterizes the relationship between differences in function values and the parameters of the response distribution. For a \textit{linear} transfer function, we propose an algorithm that achieves an error rate of $O(n^{\frac{3}{2}}/\sqrt{T})$, where $n$ is the size of the ground set and $T$ denotes the number of oracle calls. We establish a lower bound: Under the constraint that differences between queried sets are bounded by a constant, any algorithm incurs an error of at least $\Omega(n^{\frac{3}{2}}/\sqrt{T})$. Without such a constraint, the lower bound becomes $\Omega(n/\sqrt{T})$. These results show that our algorithm is optimal up to constant factors for constrained algorithms. For a \textit{sigmoid} transfer function, we design an algorithm with an error rate of $O(n^{\frac{7}{5}}/T^{\frac{2}{5}})$, and establish lower bounds analogous to the linear case.

Primary Area: optimization

Submission Number: 25553