activity
20162026
most citedGraph magnitude homology via algebraic Morse theory

11 citations · 38 across the 20 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.DS2023

Submodular Maximization under the Intersection of Matroid and Knapsack Constraints

Yu-Ran Gu, Chao Bian, Chao Qian

Submodular maximization arises in many applications, and has attracted a lot of research attentions from various areas such as artificial intelligence, finance and operations resea…

math.OC2023

Faster Algorithms for Structured Linear and Kernel Support Vector Machines

Yuzhou Gu, Zhao Song, Lichen Zhang

Quadratic programming is a ubiquitous prototype in convex programming. Many machine learning problems can be formulated as quadratic programming, including the famous Support Vecto…

cs.DS2023★ 1 cited

Fast Sampling of -Matchings and -Edge Covers

Zongchen Chen, Yuzhou Gu

For an integer , a -matching (resp. -edge cover) of a graph is a subset of edges such that every vertex is incident with at most (resp. at l…

cs.DS2023

Optimal Bounds for Noisy Sorting

Yuzhou Gu, Yinzhan Xu

Sorting is a fundamental problem in computer science. In the classical setting, it is well-known that comparisons are both necessary and sufficient to sort…

math.PR2023★ 3 cited

Weak Recovery Threshold for the Hypergraph Stochastic Block Model

Yuzhou Gu, Yury Polyanskiy

We study the weak recovery problem on the -uniform hypergraph stochastic block model (-HSBM) with two balanced communities. In HSBM a random graph is constructed by placing h…

math.PR2023★ 3 cited

Uniqueness of BP fixed point for the Potts model and applications to community detection

Yuzhou Gu, Yury Polyanskiy

In the study of sparse stochastic block models (SBMs) one often needs to analyze a distributional recursion, known as the belief propagation (BP) recursion. Uniqueness of the fixed…

cs.LG2023★ 3 cited

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time

Yuzhou Gu, Zhao Song, Junze Yin +1

Given a matrix , the low rank matrix completion problem asks us to find a rank- approximation of as for …