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Yinzhan Xu

4 accepted papers

2026

Subquadratic Algorithms and Hardness for Attention with Any Temperature

ICLR 2026poster

Despite the popularity of the Transformer architecture, the standard algorithm for computing Attention suffers from quadratic time complexity in context length $n$. Alman and Song showed that when the head dimension $d = \Theta(\log n)$, subquadratic Attention is possible if and only if the inputs h…

Cited by 0SourceScholar
2025

Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

ICML 2025poster

We study differentially private algorithms for graph cut sparsification, a fundamental problem in algorithms, privacy, and machine learning. While significant progress has been made, the best-known private and efficient cut sparsifiers on $n$-node graphs approximate each cut within $\widetilde{O}(n^…

Cited by 0SourcePDFScholar
2025

Differentially Private Gomory-Hu Trees

NeurIPS 2025poster

Given an undirected, weighted $n$-vertex graph $G = (V, E, w)$, a Gomory-Hu tree $T$ is a weighted tree on $V$ that preserves the Min-$s$-$t$-Cut between any pair of vertices $s, t \in V$. Finding cuts in graphs is a key primitive in problems such as bipartite matching, spectral and correlation clus…

Cited by 0SourceScholar
2022

Near-Tight Algorithms for the Chamberlin-Courant and Thiele Voting Rules

IJCAI 2022poster

We present an almost optimal algorithm for the classic Chamberlin-Courant multiwinner voting rule (CC) on single-peaked preference profiles. Given n voters and m candidates, it runs in almost linear time in the input size improving the previous best O(nm^2) time algorithm. We also study multiwinner…

Cited by 11SourcePDFScholar