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Author

Trevor Vaughn

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Preprint Aug 2026

Faster Minimum k-Cut II: Near-Optimal and Deterministic for Weighted Graphs

The Minimum $k$-Cut problem asks for a minimum-weight set of edges whose removal leaves an undirected weighted graph with at least $k$ connected components. We consider only $k \ge 3$. Under the Max-Weight Clique conjecture, weighted Minimum $k$-Cut requires $n^{k-1-o(1)}$ time for every fixed $k$. The fastest previous...

Trevor Vaughn · 0 citations
Preprint Aug 2026

Faster Minimum k-Cut I: Simple and Sparse Weighted Graphs

The minimum $k$-cut problem asks for the fewest edges whose removal leaves an input graph with at least $k$ connected components. Previously, the best algorithm for simple graphs ran in $O_k(n^{(1-\varepsilon)k+O(1)})$ time~\cite{HL22}, showing that the \(n^k\) barrier can be broken up to a polynomial overhead. We give...

Jason Li, Trevor Vaughn · 0 citations
Preprint Aug 2026

Deterministic Spectral Sparsification in Almost-Linear Time for Dense Graphs

Deterministic expander decomposition, along with replacing vertices by fixed expander graphs to achieve approximate regularity, extends these algorithms to general graphs and evaluates the resulting conditional-expectation scores in two ways.

Jason Li, Trevor Vaughn · 0 citations
Preprint Aug 2026

A Simple Las Vegas Algorithm for Sparse Nonnegative Convolution

Let $A, B \in \mathbb{Z}_{\ge 0}^n$ be nonnegative vectors and let $t = |\operatorname{supp}(A \star B)|$. We give a Las Vegas algorithm that computes $A \star B$ in $O(t \log t)$ expected time. More generally, for every $0<\delta \le \frac{1}{2}$, the algorithm terminates within $O(t \log t \log \frac{1}{\delta})$ tim...

Trevor Vaughn · 0 citations

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