Optimal sampling algorithms for frequency estimation in distributed data. - Zengfeng Huang; Ke Yi 001; Yunhao Liu 001; Guihai Chen (INFOCOM, 2011)

Sampling based algorithms for quantile computation in sensor networks. - Zengfeng Huang; Lu Wang 002; Ke Yi 001; Yunhao Liu 001 (SIGMOD Conference, 2011)

Mergeable summaries. - Pankaj K. Agarwal; Graham Cormode; Zengfeng Huang; Jeff M. Phillips; Zhewei Wei; Ke Yi 001 (ACM Trans. Database Syst., 2013)

Tracking the Frequency Moments at All Times. - Zengfeng Huang; Wai Ming Tai; Ke Yi 001 (CoRR, 2014)

Communication Complexity of Approximate Matching in Distributed Graphs. - Zengfeng Huang; Bozidar Radunovic; Milan Vojnovic; Qin Zhang 001 (STACS, 2015)

Clairvoyant Mechanisms for Online Auctions. - Philipp Brandes; Zengfeng Huang; Hsin-Hao Su; Roger Wattenhofer (COCOON, 2016)

SKYPE: Top-k Spatial-keyword Publish/Subscribe Over Sliding Window. - Xiang Wang 007; Ying Zhang 001; Wenjie Zhang 001; Xuemin Lin 001; Zengfeng Huang (Proc. VLDB Endow., 2016)

Tracking Matrix Approximation over Distributed Sliding Windows. - Haida Zhang; Zengfeng Huang; Zhewei Wei; Wenjie Zhang 001; Xuemin Lin 001 (ICDE, 2017)

Efficient Matrix Sketching over Distributed Data. - Zengfeng Huang; Xuemin Lin 001; Wenjie Zhang 001; Ying Zhang 001 (PODS, 2017)

The Communication Complexity of Distributed epsilon-Approximations. - Zengfeng Huang; Ke Yi 001 (SIAM J. Comput., 2017)

Top-k spatial-keyword publish/subscribe over sliding window. - Xiang Wang 007; Wenjie Zhang 001; Ying Zhang 001; Xuemin Lin 001; Zengfeng Huang (VLDB J., 2017)

Efficient and High-Quality Seeded Graph Matching: Employing High Order Structural Information. - Haida Zhang; Zengfeng Huang; Xuemin Lin 001; Zhe Lin; Wenjie Zhang 001; Ying Zhang 001 (CoRR, 2018)

GB-KMV: An Augmented KMV Sketch for Approximate Containment Similarity Search. - Yang Yang 067; Ying Zhang 001; Wenjie Zhang 001; Zengfeng Huang (ICDE, 2019)

Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation. - Zengfeng Huang; Ziyue Huang; Yilei Wang; Ke Yi 001 (NeurIPS, 2019)

Dynamic Graph Stream Algorithms in o(n) Space. - Zengfeng Huang; Pan Peng 001 (Algorithmica, 2019)

Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks. - Zengfeng Huang; Ke Yi 001; Qin Zhang 001 (Algorithmica, 2019)

Dynamic Self-training Framework for Graph Convolutional Networks. - Ziang Zhou; Shenzhong Zhang; Zengfeng Huang (CoRR, 2019)

Higher-order Weighted Graph Convolutional Networks. - Songtao Liu; Lingwei Chen; Hanze Dong; Zihao Wang; Dinghao Wu; Zengfeng Huang (CoRR, 2019)

Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices. - Zengfeng Huang (J. Mach. Learn. Res., 2019)

PathQG: Neural Question Generation from Facts. - Siyuan Wang; Zhongyu Wei; Zhihao Fan; Zengfeng Huang; Weijian Sun; Qi Zhang 001; Xuanjing Huang 001 (EMNLP (1), 2020)

Automatic Term Name Generation for Gene Ontology: Task and Dataset. - Yanjian Zhang; Qin Chen 001; Yiteng Zhang; Zhongyu Wei; Yixu Gao; Jiajie Peng; Zengfeng Huang; Weijian Sun; Xuanjing Huang 001 (EMNLP (Findings), 2020)

Simple and Deep Graph Convolutional Networks. - Ming Chen; Zhewei Wei; Zengfeng Huang; Bolin Ding; Yaliang Li (ICML, 2020)

Joint Representation Learning of Legislator and Legislation for Roll Call Prediction. - Yuqiao Yang; Xiaoqiang Lin; Geng Lin; Zengfeng Huang; Changjian Jiang; Zhongyu Wei (IJCAI, 2020)

Personalized PageRank to a Target Node, Revisited. - Hanzhi Wang 001; Zhewei Wei; Junhao Gan; Sibo Wang 001; Zengfeng Huang (KDD, 2020)

SCE: Scalable Network Embedding from Sparsest Cut. - Shengzhong Zhang; Zengfeng Huang; Haicang Zhou; Ziang Zhou (KDD, 2020)

Correction to: Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks. - Zengfeng Huang; Ke Yi 001; Qin Zhang 001 (Algorithmica, 2020)

Compressive Privatization: Sparse Distribution Estimation under Locally Differentially Privacy. - Zhongzheng Xiong; Zengfeng Huang; Xiaojun Mao; Jian Wang 016; Shan Ying (CoRR, 2020)

Communication complexity of approximate maximum matching in the message-passing model. - Zengfeng Huang; Bozidar Radunovic; Milan Vojnovic; Qin Zhang 001 (Distributed Comput., 2020)

Graph Neural Networks Inspired by Classical Iterative Algorithms. - Yongyi Yang; Tang Liu; Yangkun Wang; Jinjing Zhou; Quan Gan; Zhewei Wei; Zheng Zhang 001; Zengfeng Huang; David Wipf (ICML, 2021)

Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space. - Menglin Yang 001; Min Zhou 006; Marcus Kalander; Zengfeng Huang; Irwin King (KDD, 2021)

Scaling Up Graph Neural Networks Via Graph Coarsening. - Zengfeng Huang; Shengzhong Zhang; Chong Xi; Tang Liu; Min Zhou 006 (KDD, 2021)

Learning Based Proximity Matrix Factorization for Node Embedding. - Xingyi Zhang 003; Kun Xie 010; Sibo Wang 001; Zengfeng Huang (KDD, 2021)

Understanding Bandits with Graph Feedback. - Houshuang Chen; Zengfeng Huang; Shuai Li 010; Chihao Zhang 001 (NeurIPS, 2021)

BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation. - Mingguo He; Zhewei Wei; Zengfeng Huang; Hongteng Xu (NeurIPS, 2021)

Batched Lipschitz Bandits. - Yasong Feng; Zengfeng Huang; Tianyu Wang 008 (CoRR, 2021)

Implicit vs Unfolded Graph Neural Networks. - Yongyi Yang; Yangkun Wang; Zengfeng Huang; David Wipf (CoRR, 2021)

Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA. - Zengfeng Huang; Xuemin Lin 001; Wenjie Zhang 001; Ying Zhang 001 (J. Mach. Learn. Res., 2021)

Efficient and High-Quality Seeded Graph Matching: Employing Higher-order Structural Information. - Haida Zhang; Zengfeng Huang; Xuemin Lin 001; Zhe Lin; Wenjie Zhang 001; Ying Zhang 001 (ACM Trans. Knowl. Discov. Data, 2021)

Why Propagate Alone? Parallel Use of Labels and Features on Graphs. - Yangkun Wang; Jiarui Jin; Weinan Zhang 001; Yongyi Yang; Jiuhai Chen; Quan Gan; Yong Yu 001; Zheng Zhang 001; Zengfeng Huang; David Wipf (ICLR, 2022)

Optimal Clustering with Noisy Queries via Multi-Armed Bandit. - Jinghui Xia; Zengfeng Huang (ICML, 2022)

Transformers from an Optimization Perspective. - Yongyi Yang; Zengfeng Huang; David P. Wipf (NeurIPS, 2022)

BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction. - Bisheng Li; Min Zhou 006; Shengzhong Zhang; Menglin Yang 001; Defu Lian; Zengfeng Huang (SIGIR, 2022)

Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy. - Zhongzheng Xiong; Jialin Sun; Xiaojun Mao; Jian Wang 016; Shan Ying; Zengfeng Huang (WWW, 2022)

Exploiting Neighbor Effect: Conv-Agnostic GNNs Framework for Graphs with Heterophily. - Jie Chen; Shouzhen Chen; Zengfeng Huang; Junping Zhang; Jian Pu (CoRR, 2022)

ASGNN: Graph Neural Networks with Adaptive Structure. - Zepeng Zhang; Songtao Lu; Zengfeng Huang; Ziping Zhao 002 (CoRR, 2022)

On Coresets for Clustering in Small Dimensional Euclidean spaces. - Lingxiao Huang; Ruiyuan Huang; Zengfeng Huang; Xuan Wu 002 (ICML, 2023)

Adversarially Robust Distributed Count Tracking via Partial Differential Privacy. - Zhongzheng Xiong; Xiaoyi Zhu; Zengfeng Huang (NeurIPS, 2023)

Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition. - Divin Yan; Gengchen Wei; Chen Yang; Shengzhong Zhang; Zengfeng Huang (NeurIPS, 2023)

Visual Analytics for Phishing Scam Identification in Blockchain Transactions with Multiple Model Comparison. - Jiaqi Dong; Zishu Qin; Zhou Fang; Xuan Chen; Zengfeng Huang; Haoyun Guo; Richen Liu; Cagatay Turkay; Siming Chen 001 (VINCI, 2023)

ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training. - Kezhao Huang; Haitian Jiang; Minjie Wang; Guangxuan Xiao; David Wipf; Xiang Song 003; Quan Gan; Zengfeng Huang; Jidong Zhai; Zheng Zhang 001 (CoRR, 2023)

UNREAL: Unlabeled Nodes Retrieval and Labeling for Heavily-imbalanced Node Classification. - Liang Yan; Shengzhong Zhang; Bisheng Li; Min Zhou 006; Zengfeng Huang (CoRR, 2023)

Understanding Community Bias Amplification in Graph Representation Learning. - Shengzhong Zhang; Wenjie Yang 006; Yimin Zhang; Hongwei Zhang; Divin Yan; Zengfeng Huang (CoRR, 2023)

Effective stabilized self-training on few-labeled graph data. - Ziang Zhou; Jieming Shi 001; Shengzhong Zhang; Zengfeng Huang; Qing Li 001 (Inf. Sci., 2023)

Efficient Tree-SVD for Subset Node Embedding over Large Dynamic Graphs. - Xinyu Du; Xingyi Zhang 003; Sibo Wang 001; Zengfeng Huang (Proc. ACM Manag. Data, 2023)

Learning Regularized Noise Contrastive Estimation for Robust Network Embedding. - Hao Xiong 003; Junchi Yan; Zengfeng Huang (IEEE Trans. Knowl. Data Eng., 2023)

The Communication Complexity of Distributed Maximization. - Yuxiang Tian; Xiaoyi Zhu; Zengfeng Huang (COCOON (1), 2024)

Enhancing Performance of Coarsened Graphs with Gradient-Matching. - Wenjie Yang; Shengzhong Zhang; Zengfeng Huang (ICASSP, 2024)

StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning. - Shengzhong Zhang; Wenjie Yang 006; Xinyuan Cao; Hongwei Zhang; Zengfeng Huang (ICLR, 2024)

Distributed Thresholded Counting with Limited Interaction. - Xiaoyi Zhu; Yuxiang Tian; Zengfeng Huang (KDD, 2024)

Your Graph Recommender is Provably a Single-view Graph Contrastive Learning. - Wenjie Yang; Shengzhong Zhang; Jiaxing Guo; Zengfeng Huang (CoRR, 2024)

High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context Distributions. - Ruiyuan Huang; Zengfeng Huang (CoRR, 2024)

Lipschitz Bandits With Batched Feedback. - Yasong Feng; Zengfeng Huang; Tianyu Wang 008 (IEEE Trans. Inf. Theory, 2024)

FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training. - Kezhao Huang; Haitian Jiang; Minjie Wang; Guangxuan Xiao; David Wipf; Xiang Song 003; Quan Gan; Zengfeng Huang; Jidong Zhai; Zheng Zhang 001 (Proc. VLDB Endow., 2024)

Optimal Matrix Sketching over Sliding Windows. - Hanyan Yin; Dongxie Wen; Jiajun Li; Zhewei Wei; Xiao Zhang 001; Zengfeng Huang; Feifei Li 001 (Proc. VLDB Endow., 2024)

Exploiting Neighbor Effect: Conv-Agnostic GNN Framework for Graphs With Heterophily. - Jie Chen; Shouzhen Chen; Junbin Gao; Zengfeng Huang; Junping Zhang; Jian Pu (IEEE Trans. Neural Networks Learn. Syst., 2024)

HAF-RM: A Hybrid Alignment Framework for Reward Model Training. - Shujun Liu; Xiaoyu Shen; Yuhang Lai; Siyuan Wang; Shengbin Yue; Zengfeng Huang; Xuanjing Huang 001; Zhongyu Wei (ACL (1), 2025)

Optimal Framework for Clustering with Noisy Queries. - Jinghui Xia; Zengfeng Huang (COCOON (1), 2025)

TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics. - Lu Yi 002; Jie Peng 005; Yanping Zheng; Fengran Mo; Zhewei Wei; Yuhang Ye 002; Yue Zixuan; Zengfeng Huang (ICLR, 2025)

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy. - Haitian Jiang; Renjie Liu 001; Zengfeng Huang; Yichuan Wang 002; Xiao Yan 002; Zhenkun Cai; Minjie Wang; David Wipf (ICLR, 2025)

Lipschitz Bandits in Optimal Space. - Xiaoyi Zhu; Zengfeng Huang (ICLR, 2025)

Simple and Optimal Algorithms for Heavy Hitters and Frequency Moments in Distributed Models. - Zengfeng Huang; Zhongzheng Xiong; Xiaoyi Zhu; Zhewei Wei (STOC, 2025)

I2HGNN: Iterative Interpretable HyperGraph Neural Network for semi-supervised classification. - Hongwei Zhang; Saizhuo Wang; Zixin Hu; Yuan Qi; Zengfeng Huang; Jian Guo (Neural Networks, 2025)

Graph Batch Coarsening framework for scalable graph neural networks. - Shengzhong Zhang; Yimin Zhang; Bisheng Li; Wenjie Yang 006; Min Zhou 006; Zengfeng Huang (Neural Networks, 2025)

Graph Neural Networks With Adaptive Structures. - Zepeng Zhang; Songtao Lu; Zengfeng Huang; Ziping Zhao 002 (IEEE J. Sel. Top. Signal Process., 2025)

Nearly Tight Bounds for Cross-Learning Contextual Bandits with Graphical Feedback. - Ruiyuan Huang; Zengfeng Huang (CoRR, 2025)

Right Is Not Enough: The Pitfalls of Outcome Supervision in Training LLMs for Math Reasoning. - Jiaxing Guo; Wenjie Yang; Shengzhong Zhang; Tongshan Xu; Lun Du; Da Zheng; Zengfeng Huang (CoRR, 2025)

Beyond Homogeneous Attention: Memory-Efficient LLMs via Fourier-Approximated KV Cache. - Xiaoran Liu; Siyang He; Qiqi Wang 014; Ruixiao Li; Yuerong Song; Zhigeng Liu; Linlin Li 001; Qun Liu 001; Zengfeng Huang; Qipeng Guo; Ziwei He; Xipeng Qiu (CoRR, 2025)

LongLLaDA: Unlocking Long Context Capabilities in Diffusion LLMs. - Xiaoran Liu; Zhigeng Liu; Zengfeng Huang; Qipeng Guo; Ziwei He; Xipeng Qiu (CoRR, 2025)

Space Complexity of Euclidean Clustering. - Xiaoyi Zhu; Yuxiang Tian; Lingxiao Huang; Zengfeng Huang (IEEE Trans. Inf. Theory, 2025)

Sparse-dLLM: Accelerating Diffusion LLMs with Dynamic Cache Eviction. - Yuerong Song; Xiaoran Liu; Ruixiao Li; Zhigeng Liu; Zengfeng Huang; Qipeng Guo; Ziwei He; Xipeng Qiu (CoRR, 2025)