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Preprint Oct 2026

0.4633-Approximation for Online and Offline on-Monotone DR-Submodular Maximization

We obtain the approximation coefficient $\alpha_0=54440750000/117486474169>0.463378$ for maximizing nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the unit cube, with queries allowed throughout the cube. This improves the previous best coefficient, $4/9$. A coordinatewise m...

Vaneet Aggarwal, D. Du · 0 citations
Preprint Oct 2026

A 0.4584-approximation for DR-submodular maximization over down-closed convex sets

We obtain a $0.4584$-approximation for nonnegative, non-monotone, $L$-smooth DR-submodular maximization over compact convex down-closed subsets of the unit cube, improving the $4/9\approx0.4444$ ratio of Aggarwal's projection-based algorithm~\cite{aggarwal2026geometry}. A recovery map combining exponential and linear-f...

D. Du · 0 citations
Preprint Oct 2026

Concave Roofs and Downward Recovery for DR-Submodular Polynomial Maximization

Global monotonicity and concave-cardinality structure give stronger guarantees for multilinear local-function sums, with no recovery beyond the identity map, and standard matroid rounding transfers the multilinear guarantees without loss.

D. Du · 1 citation

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