402 citations · 556 across the 19 of their papers we have counts for
19 papers
On Coresets for Clustering in Small Dimensional Euclidean Spaces
Lingxiao Huang, Ruiyuan Huang, Zengfeng Huang +1
We consider the problem of constructing small coresets for -Median in Euclidean spaces. Given a large set of data points , a coreset is a much smaller set…
Optimal Clustering with Noisy Queries via Multi-Armed Bandit
Jinghui Xia, Zengfeng Huang
Motivated by many applications, we study clustering with a faulty oracle. In this problem, there are items belonging to unknown clusters, and the algorithm is allowed to as…
Lipschitz Bandits with Batched Feedback
Yasong Feng, Zengfeng Huang, Tianyu Wang
In this paper, we study Lipschitz bandit problems with batched feedback, where the expected reward is Lipschitz and the reward observations are communicated to the player in batche…
One-Bit Matrix Completion with Differential Privacy
Zhengpin Li, Zheng Wei, Zengfeng Huang +2
As a prevailing collaborative filtering method for recommendation systems, one-bit matrix completion requires data collected by users to provide personalized service. Due to insidi…
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang +6
Despite the recent success of graph neural networks (GNN), common architectures often exhibit significant limitations, including sensitivity to oversmoothing, long-range dependenci…
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy
Zhongzheng Xiong, Jialin Sun, Xiaojun Mao +3
Recent years, local differential privacy (LDP) has been adopted by many web service providers like Google \cite{erlingsson2014rappor}, Apple \cite{apple2017privacy} and Microsoft \…
Simple and Deep Graph Convolutional Networks
Ming Chen, Zhewei Wei, Zengfeng Huang +2
Graph convolutional networks (GCNs) are a powerful deep learning approach for graph-structured data. Recently, GCNs and subsequent variants have shown superior performance in vario…
Personalized PageRank to a Target Node, Revisited
Hanzhi Wang, Zhewei Wei, Junhao Gan +2
Personalized PageRank (PPR) is a widely used node proximity measure in graph mining and network analysis. Given a source node and a target node , the PPR value repr…
SCE: Scalable Network Embedding from Sparsest Cut
Shengzhong Zhang, Zengfeng Huang, Haicang Zhou +1
Large-scale network embedding is to learn a latent representation for each node in an unsupervised manner, which captures inherent properties and structural information of the unde…
Ghost imaging based on Y-net: a dynamic coding and conjugate-decoding approach
Ruiguo Zhu, Hong Yu, Zhijie Tan +4
Ghost imaging incorporating deep learning technology has recently attracted much attention in the optical imaging field. However, deterministic illumination and multiple exposure a…
Higher-order Weighted Graph Convolutional Networks
Songtao Liu, Lingwei Chen, Hanze Dong +3
Graph Convolution Network (GCN) has been recognized as one of the most effective graph models for semi-supervised learning, but it extracts merely the first-order or few-order neig…
Optimization of light fields in ghost imaging using dictionary learning
Chenyu Hu, Zhisheng Tong, Zhentao Liu +3
Ghost imaging (GI) is a novel imaging technique based on the second-order correlation of light fields. Due to limited number of samplings in practice, traditional GI methods often…
Efficient and High-Quality Seeded Graph Matching: Employing High Order Structural Information
Haida Zhang, Zengfeng Huang, Xuemin Lin +3
Driven by many real applications, we study the problem of seeded graph matching. Given two graphs and , and a small set of pre-matched node…
GB-KMV: An Augmented KMV Sketch for Approximate Containment Similarity Search
Yang Yang, Ying Zhang, Wenjie Zhang +1
In this paper, we study the problem of approximate containment similarity search. Given two records Q and X, the containment similarity between Q and X with respect to Q is |Q inte…
Communication complexity of approximate maximum matching in the message-passing model
Zengfeng Huang, Bozidar Radunovic, Milan Vojnovic +1
We consider the communication complexity of finding an approximate maximum matching in a graph in a multi-party message-passing communication model. The maximum matching problem is…
Top-k Spatial-keyword Publish/Subscribe Over Sliding Window
Xiang Wang, Ying Zhang, Wenjie Zhang +2
With the prevalence of social media and GPS-enabled devices, a massive amount of geo-textual data has been generated in a stream fashion, leading to a variety of applications such…
Dynamic Graph Stream Algorithms in Space
Zengfeng Huang, Pan Peng
In this paper we study graph problems in dynamic streaming model, where the input is defined by a sequence of edge insertions and deletions. As many natural problems require …
Tracking the Frequency Moments at All Times
Zengfeng Huang, Wai Ming Tai, Ke Yi
The traditional requirement for a randomized streaming algorithm is just {\em one-shot}, i.e., algorithm should be correct (within the stated $\eps$-error bound) at the end of the…
Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks
Zengfeng Huang, Ke Yi, Qin Zhang
We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the {\em count-tracking} problem, where there a…