Huang, Zengfeng

25 publications

NeurIPS 2025 Geometric Imbalance in Semi-Supervised Node Classification Liang Yan, Shengzhong Zhang, Bisheng Li, Menglin Yang, Chen Yang, Min Zhou, Weiyang Ding, Yutong Xie, Zengfeng Huang

ICML 2025 High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context Distributions Ruiyuan Huang, Zengfeng Huang

JMLR 2025 Implicit vs Unfolded Graph Neural Networks Yongyi Yang, Tang Liu, Yangkun Wang, Zengfeng Huang, David Wipf

ICLR 2025 Lipschitz Bandits in Optimal Space Xiaoyi Zhu, Zengfeng Huang

ICLR 2025 MuseGNN: Forming Scalable, Convergent GNN Layers That Minimize a Sampling-Based Energy Haitian Jiang, Renjie Liu, Zengfeng Huang, Yichuan Wang, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf

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

TMLR 2025 Understanding Class Bias Amplification in Graph Representation Learning Shengzhong Zhang, Wenjie Yang, Yimin Zhang, Hongwei Zhang, Zengfeng Huang

ICLR 2024 StructComp: Substituting Propagation with Structural Compression in Training Graph Contrastive Learning Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang

NeurIPS 2023 Adversarially Robust Distributed Count Tracking via Partial Differential Privacy Zhongzheng Xiong, Xiaoyi Zhu, Zengfeng Huang

ICML 2023 On Coresets for Clustering in Small Dimensional Euclidean Spaces Lingxiao Huang, Ruiyuan Huang, Zengfeng Huang, Xuan Wu

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

ICMLW 2022 Enhancing Multi-Hop Connectivity for Graph Convolutional Networks Songtao Liu, Shixiong Jing, Tong Zhao, Zengfeng Huang, Dinghao Wu

NeurIPS 2022 Lipschitz Bandits with Batched Feedback Yasong Feng, Zengfeng Huang, Tianyu Wang

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

NeurIPS 2022 Transformers from an Optimization Perspective Yongyi Yang, Zengfeng Huang, David P Wipf

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

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

JMLR 2021 Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA Zengfeng Huang, Xuemin Lin, Wenjie Zhang, Ying Zhang

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

NeurIPS 2021 Understanding Bandits with Graph Feedback Houshuang Chen, Zengfeng Huang, Shuai Li, Chihao Zhang

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

ICML 2020 Simple and Deep Graph Convolutional Networks Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, Yaliang Li

JMLR 2019 Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices Zengfeng Huang

NeurIPS 2019 Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation Zengfeng Huang, Ziyue Huang, Yilei Wang, Ke Yi

ICML 2018 Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices Zengfeng Huang