3 citations · 3 across the 8 of their papers we have counts for
7 papers · 1 filter
Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
Jiale Cheng, Ziao Wang, Lei Ying
This paper studies graph matching under the correlated (ER) graph pair model. This model first samples an base graph, whose edges a…
Diffusion-Network Alignment: An Efficient Algorithm and Explicit Probability Bounds
Ziao Wang, Lei Ying
This paper studies a variation of the classic network alignment problem, named diffusion-network alignment. The goal is to align the vertices of a rooted diffusion tree to the vert…
Noisy Computing of the Threshold Function
Ziao Wang, Nadim Ghaddar, Banghua Zhu +1
Let denote the -out-of- threshold function: given input Boolean variables, the output is if and only if at least of the inputs are . We conside…
Noisy Computing of the and Functions
Banghua Zhu, Ziao Wang, Nadim Ghaddar +2
We consider the problem of computing a function of variables using noisy queries, where each query is incorrect with some fixed and known probability . Specifica…
Efficient Algorithms for Attributed Graph Alignment with Vanishing Edge Correlation
Ziao Wang, Weina Wang, Lele Wang
Graph alignment refers to the task of finding the vertex correspondence between two correlated graphs of vertices. Extensive study has been done on polynomial-time algorithms f…
On the Optimal Bounds for Noisy Computing
Banghua Zhu, Ziao Wang, Nadim Ghaddar +2
We revisit the problem of computing with noisy information considered in Feige et al. 1994, which includes computing the OR function from noisy queries, and computing the MAX, SEAR…
On the Feasible Region of Efficient Algorithms for Attributed Graph Alignment
Ziao Wang, Ning Zhang, Weina Wang +1
Graph alignment aims at finding the vertex correspondence between two correlated graphs, a task that frequently occurs in graph mining applications such as social network analysis.…