Feature Selection with Particle Swarms. - Yu Liu 035; Zheng Qin; Zenglin Xu; Xingshi He (CIS, 2004)

Kernel Maximum a Posteriori Classification with Error Bound Analysis. - Zenglin Xu; Kaizhu Huang; Jianke Zhu; Irwin King; Michael R. Lyu (ICONIP (1), 2007)

Maximum Margin based Semi-supervised Spectral Kernel Learning. - Zenglin Xu; Jianke Zhu; Michael R. Lyu; Irwin King (IJCNN, 2007)

Efficient Convex Relaxation for Transductive Support Vector Machine. - Zenglin Xu; Rong Jin 001; Jianke Zhu; Irwin King; Michael R. Lyu (NIPS, 2007)

Web page classification with heterogeneous data fusion. - Zenglin Xu; Irwin King; Michael R. Lyu (WWW, 2007)

Feature Selection Based on Minimum Error minimax Probability Machine. - Zenglin Xu; Irwin King; Michael R. Lyu (Int. J. Pattern Recognit. Artif. Intell., 2007)

Semi-supervised text categorization by active search. - Zenglin Xu; Rong Jin 001; Kaizhu Huang; Michael R. Lyu; Irwin King (CIKM, 2008)

An Effective Approach to 3D Deformable Surface Tracking. - Jianke Zhu; Steven C. H. Hoi; Zenglin Xu; Michael R. Lyu (ECCV (3), 2008)

Semi-supervised Learning from General Unlabeled Data. - Kaizhu Huang; Zenglin Xu; Irwin King; Michael R. Lyu (ICDM, 2008)

An Extended Level Method for Efficient Multiple Kernel Learning. - Zenglin Xu; Rong Jin 001; Irwin King; Michael R. Lyu (NIPS, 2008)

Non-monotonic feature selection. - Zenglin Xu; Rong Jin 001; Jieping Ye; Michael R. Lyu; Irwin King (ICML, 2009)

Supervised Self-taught Learning: Actively transferring knowledge from unlabeled data. - Kaizhu Huang; Zenglin Xu; Irwin King; Michael R. Lyu; Colin Campbell (IJCNN, 2009)

Adaptive Regularization for Transductive Support Vector Machine. - Zenglin Xu; Rong Jin 001; Jianke Zhu; Irwin King; Michael R. Lyu; Zhirong Yang (NIPS, 2009)

Heavy-Tailed Symmetric Stochastic Neighbor Embedding. - Zhirong Yang; Irwin King; Zenglin Xu; Erkki Oja (NIPS, 2009)

A novel kernel-based maximum a posteriori classification method. - Zenglin Xu; Kaizhu Huang; Jianke Zhu; Irwin King; Michael R. Lyu (Neural Networks, 2009)

Smooth Optimization for Effective Multiple Kernel Learning. - Zenglin Xu; Rong Jin 001; Shenghuo Zhu; Michael R. Lyu; Irwin King (AAAI, 2010)

Simple and Efficient Multiple Kernel Learning by Group Lasso. - Zenglin Xu; Rong Jin 001; Haiqin Yang; Irwin King; Michael R. Lyu (ICML, 2010)

Online Learning for Group Lasso. - Haiqin Yang; Zenglin Xu; Irwin King; Michael R. Lyu (ICML, 2010)

Robust Metric Learning by Smooth Optimization. - Kaizhu Huang; Rong Jin 001; Zenglin Xu; Cheng-Lin Liu 001 (UAI, 2010)

Discriminative semi-supervised feature selection via manifold regularization. - Zenglin Xu; Irwin King; Michael R. Lyu; Rong Jin 001 (IEEE Trans. Neural Networks, 2010)

Sparse Matrix-Variate t Process Blockmodels. - Zenglin Xu; Feng Yan 003; Yuan (Alan) Qi (AAAI, 2011)

Sparse matrix-variate Gaussian process blockmodels for network modeling. - Feng Yan 003; Zenglin Xu; Yuan (Alan) Qi (UAI, 2011)

InfTucker: t-Process based Infinite Tensor Decomposition - Zenglin Xu; Feng Yan 003; Yuan (Alan) Qi (CoRR, 2011)

Efficient Sparse Generalized Multiple Kernel Learning. - Haiqin Yang; Zenglin Xu; Jieping Ye; Irwin King; Michael R. Lyu (IEEE Trans. Neural Networks, 2011)

Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis. - Zenglin Xu; Feng Yan 003; Yuan (Alan) Qi (ICML, 2012)

Exact and Stable Recovery of Pairwise Interaction Tensors. - Shouyuan Chen; Michael R. Lyu; Irwin King; Zenglin Xu (NIPS, 2013)

Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis - Shandian Zhe; Zenglin Xu; Yuan Qi 001; Peng Yu (CoRR, 2013)

Detecting Insider Information Theft Using Features from File Access Logs. - Christopher S. Gates; Ninghui Li; Zenglin Xu; Suresh N. Chari; Ian M. Molloy; Youngja Park (ESORICS (2), 2014)

Kernel tapering: A simple and effective approach to sparse kernels for image processing. - Bin Shen 002; Zenglin Xu; Jan P. Allebach (ICIP, 2014)

Non-monotonic Feature Selection for Regression. - Haiqin Yang; Zenglin Xu; Irwin King; Michael R. Lyu (ICONIP (2), 2014)

Joint Association Discovery and Diagnosis of Alzheimer's Disease by Supervised Heterogeneous Multiview Learning. - Shandian Zhe; Zenglin Xu; Yuan Qi 001; Peng Yu (Pacific Symposium on Biocomputing, 2014)

Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation. - Zenglin Xu; Rong Jin 001; Bin Shen 002; Shenghuo Zhu (AAAI, 2015)

Sparse Bayesian Multiview Learning for Simultaneous Association Discovery and Diagnosis of Alzheimer's Disease. - Shandian Zhe; Zenglin Xu; Yuan Qi 001; Peng Yu (AAAI, 2015)

Scalable Nonparametric Multiway Data Analysis. - Shandian Zhe; Zenglin Xu; Xinqi Chu; Yuan (Alan) Qi; Youngja Park (AISTATS, 2015)

Learning from Others: User Anomaly Detection Using Anomalous Samples from Other Users. - Youngja Park; Ian M. Molloy; Suresh N. Chari; Zenglin Xu; Christopher S. Gates; Ninghui Li (ESORICS (2), 2015)

Budget constrained non-monotonic feature selection. - Haiqin Yang; Zenglin Xu; Michael R. Lyu; Irwin King (Neural Networks, 2015)

Bayesian Nonparametric Models for Multiway Data Analysis. - Zenglin Xu; Feng Yan 003; Yuan (Alan) Qi (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Learning with Marginalized Corrupted Features and Labels Together. - Yingming Li; Ming Yang 012; Zenglin Xu; Zhongfei (Mark) Zhang (AAAI, 2016)

DinTucker: Scaling Up Gaussian Process Models on Large Multidimensional Arrays. - Shandian Zhe; Yuan Qi 001; Youngja Park; Zenglin Xu; Ian M. Molloy; Suresh Chari (AAAI, 2016)

Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network. - Haoli Bai; Zenglin Xu; Bin Liu 022; Yingming Li (ACML, 2016)

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing. - Linnan Wang; Wei Wu 016; Zenglin Xu; Jianxiong Xiao; Yi Yang 018 (ICS, 2016)

Multi-View Learning with Limited and Noisy Tagging. - Yingming Li; Ming Yang 012; Zenglin Xu; Zhongfei (Mark) Zhang (IJCAI, 2016)

Consensus Guided Multiple Match Removal for Geometry Verification in Image Retrieval. - Hong Wu; Xing Heng; Zenglin Xu (MMM (2), 2016)

Distributed Flexible Nonlinear Tensor Factorization. - Shandian Zhe; Kai Zhang 001; Pengyuan Wang 001; Kuang-chih Lee; Zenglin Xu; Yuan Qi 001; Zoubin Ghahramani (NIPS, 2016)

Distributed Flexible Nonlinear Tensor Factorization. - Shandian Zhe; Pengyuan Wang 001; Kuang-chih Lee; Zenglin Xu; Jian Yang 002; Youngja Park; Yuan Qi 001 (CoRR, 2016)

Association Discovery and Diagnosis of Alzheimer's Disease with Bayesian Multiview Learning. - Zenglin Xu; Shandian Zhe; Yuan Qi 001; Peng Yu (J. Artif. Intell. Res., 2016)

Manifold regularized matrix completion for multilabel classification. - Bin Liu 022; Zenglin Xu; Shuang Wu; Fei Wang 001 (Pattern Recognit. Lett., 2016)

Learning with Feature Network and Label Network Simultaneously. - Yingming Li; Ming Yang 012; Zenglin Xu; Zhongfei (Mark) Zhang (AAAI, 2017)

Regularized Multi-source Matrix Factorization for Diagnosis of Alzheimer's Disease. - Xiaofan Que; Yazhou Ren 001; Jiayu Zhou; Zenglin Xu (ICONIP (1), 2017)

Robust Softmax Regression for Multi-class Classification with Self-Paced Learning. - Yazhou Ren 001; Peng Zhao; Yongpan Sheng; Dezhong Yao 001; Zenglin Xu (IJCAI, 2017)

Nonnegative matrix factorization with adaptive neighbors. - Shudong Huang; Zenglin Xu; Fei Wang 001 (IJCNN, 2017)

Simple and efficient parallelization for probabilistic temporal tensor factorization. - Guangxi Li; Zenglin Xu; Linnan Wang; Jinmian Ye; Irwin King; Michael R. Lyu (IJCNN, 2017)

Learning from semantically dependent multi-tasks. - Bin Liu 022; Zenglin Xu; Bo Dai 001; Haoli Bai; Xianghong Fang; Yazhou Ren 001; Shandian Zhe (IJCNN, 2017)

Balanced self-paced learning with feature corruption. - Yazhou Ren 001; Peng Zhao; Zenglin Xu; Dezhong Yao 001 (IJCNN, 2017)

Link prediction by exploiting network formation games in exchangeable graphs. - Liqiang Wang; Yafang Wang; Bin Liu 022; Lirong He; Shijun Liu; Gerard de Melo; Zenglin Xu (IJCNN, 2017)

Efficient Communications in Training Large Scale Neural Networks. - Yiyang Zhao; Linnan Wang; Wei Wu 016; George Bosilca; Richard W. Vuduc; Jinmian Ye; Wenqi Tang; Zenglin Xu (ACM Multimedia (Thematic Workshops), 2017)

Stochastic Sequential Neural Networks with Structured Inference. - Hao Liu; Haoli Bai; Lirong He; Zenglin Xu (CoRR, 2017)

Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs. - Dan Ma 005; Bin Liu 022; Zhao Kang 001; Jianke Zhu; Zenglin Xu (CoRR, 2017)

BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition. - Guangxi Li; Jinmian Ye; Haiqin Yang; Di Chen; Shuicheng Yan; Zenglin Xu (CoRR, 2017)

Unified Spectral Clustering With Optimal Graph. - Zhao Kang 001; Chong Peng 001; Qiang Cheng 001; Zenglin Xu (AAAI, 2018)

Learning With Incomplete Labels. - Yingming Li; Zenglin Xu; Zhongfei Zhang (AAAI, 2018)

Neural Relational Topic Models for Scientific Article Analysis. - Haoli Bai; Zhuangbin Chen; Michael R. Lyu; Irwin King; Zenglin Xu (CIKM, 2018)

Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition. - Jinmian Ye; Linnan Wang; Guangxi Li; Di Chen; Shandian Zhe; Xinqi Chu; Zenglin Xu (CVPR, 2018)

Self-Paced Multi-Task Multi-View Capped-norm Clustering. - Yazhou Ren 001; Xin Yan; Zechuan Hu; Zenglin Xu (ICONIP (4), 2018)

Association Study of Alzheimer's Disease with Tree-Guided Sparse Canonical Correlation Analysis. - Shangchen Zhou; Shuai Yuan 018; Zhizhuo Zhang; Zenglin Xu (ICONIP (7), 2018)

Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. - Zhao Kang 001; Xiao Lu 004; Jinfeng Yi; Zenglin Xu (IJCAI, 2018)

Structured Inference for Recurrent Hidden Semi-markov Model. - Hao Liu; Lirong He; Haoli Bai; Bo Dai 001; Kun Bai; Zenglin Xu (IJCAI, 2018)

Mark-Guided Segmentation of Ultrasonic Thyroid Nodules Using Deep Learning. - Shujun Zhou; Hong Wu; Jie Gong; Ting Le; Hao Wu; Qin Chen; Zenglin Xu (ISICDM, 2018)

Visualizing Multi-document Semantics via Open Domain Information Extraction. - Yongpan Sheng; Zenglin Xu; Yafang Wang; Xiangyu Zhang; Jia Jia; Zhonghui You; Gerard de Melo (ECML/PKDD (3), 2018)

Superneurons: dynamic GPU memory management for training deep neural networks. - Linnan Wang; Jinmian Ye; Yiyang Zhao; Wei Wu 016; Ang Li 006; Shuaiwen Leon Song; Zenglin Xu; Tim Kraska (PPoPP, 2018)

Semi-supervised DenPeak Clustering with Pairwise Constraints. - Yazhou Ren 001; Xiaohui Hu; Ke Shi; Guoxian Yu; Dezhong Yao 001; Zenglin Xu (PRICAI (1), 2018)

Knowledge Base Completion by Variational Bayesian Neural Tensor Decomposition. - Lirong He; Bin Liu 022; Guangxi Li; Yongpan Sheng; Yafang Wang; Zenglin Xu (Cogn. Comput., 2018)

NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition. - Bin Liu 022; Lirong He; Yingming Li; Shandian Zhe; Zenglin Xu (Cogn. Comput., 2018)

Latent Dirichlet Allocation in Generative Adversarial Networks. - Lili Pan 001; Shen Cheng; Jian Liu; Yazhou Ren 001; Zenglin Xu (CoRR, 2018)

Robust graph regularized nonnegative matrix factorization for clustering. - Shudong Huang; Hongjun Wang 002; Tao Li 001; Tianrui Li 001; Zenglin Xu (Data Min. Knowl. Discov., 2018)

TensorD: A tensor decomposition library in TensorFlow. - Liyang Hao; Siqi Liang 001; Jinmian Ye; Zenglin Xu (Neurocomputing, 2018)

Robust multi-view data clustering with multi-view capped-norm K-means. - Shudong Huang; Yazhou Ren 001; Zenglin Xu (Neurocomputing, 2018)

Self-weighted multi-view clustering with soft capped norm. - Shudong Huang; Zhao Kang 001; Zenglin Xu (Knowl. Based Syst., 2018)

Adaptive local structure learning for document co-clustering. - Shudong Huang; Zenglin Xu; Jiancheng Lv 001 (Knowl. Based Syst., 2018)

Manifold regularized matrix completion for multi-label learning with ADMM. - Bin Liu 022; Yingming Li; Zenglin Xu (Neural Networks, 2018)

Similarity Learning via Kernel Preserving Embedding. - Zhao Kang 001; Yiwei Lu; Yuanzhang Su; Changsheng Li; Zenglin Xu (AAAI, 2019)

Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition. - Yu Pan 005; Jing Xu; Maolin Wang 001; Jinmian Ye; Fei Wang 001; Kun Bai; Zenglin Xu (AAAI, 2019)

Constructing Interpretive Spatio-Temporal Features for Multi-Turn Responses Selection. - Junyu Lu; Chenbin Zhang; Zeying Xie; Guang Ling; Tom Chao Zhou; Zenglin Xu (ACL (1), 2019)

Coherence and Salience-Based Multi-Document Relationship Mining. - Yongpan Sheng; Zenglin Xu (APWeb/WAIM (1), 2019)

Machine Reading Comprehension: Matching and Orders. - Ao Liu 008; Lizhen Qu; Junyu Lu; Chenbin Zhang; Zenglin Xu (CIKM, 2019)

Additive Adversarial Learning for Unbiased Authentication. - Jian Liang 002; Yuren Cao; Chenbin Zhang; Shiyu Chang; Kun Bai; Zenglin Xu (CVPR, 2019)

A Two-Stage Multi-task Learning-Based Method for Selective Unsupervised Domain Adaptation. - Yong Dai 001; Jian Zhang; Shuai Yuan 018; Zenglin Xu (ICDM Workshops, 2019)

Deep Minimax Probability Machine. - Lirong He; Ziyi Guo; Kaizhu Huang; Zenglin Xu (ICDM Workshops, 2019)

Adversarial Noise Layer: Regularize Neural Network by Adding Noise. - Zhonghui You; Jinmian Ye; Kunming Li; Zenglin Xu; Ping Wang 003 (ICIP, 2019)

Multiple Partitions Aligned Clustering. - Zhao Kang 001; Zipeng Guo; Shudong Huang; Siying Wang 002; Wenyu Chen 001; Yuanzhang Su; Zenglin Xu (IJCAI, 2019)

Tensor Ring Restricted Boltzmann Machines. - Maolin Wang 001; Chenbin Zhang; Yu Pan 005; Jing Xu; Zenglin Xu (IJCNN, 2019)

Structured Pruning of Recurrent Neural Networks through Neuron Selection. - Liangjiang Wen; Xueyang Zhang; Haoli Bai; Zenglin Xu (CoRR, 2019)

A New Corpus for Low-Resourced Sindhi Language with Word Embeddings. - Wazir Ali; Jay Kumar; Junyu Lu; Zenglin Xu (CoRR, 2019)

Structure Learning with Similarity Preserving. - Zhao Kang 001; Xiao Lu 004; Yiwei Lu; Chong Peng 001; Zenglin Xu (CoRR, 2019)

Clustering with similarity preserving. - Zhao Kang 001; Honghui Xu; Boyu Wang 004; Hongyuan Zhu; Zenglin Xu (Neurocomputing, 2019)

Semi-supervised deep embedded clustering. - Yazhou Ren 001; Kangrong Hu; Xinyi Dai; Lili Pan 001; Steven C. H. Hoi; Zenglin Xu (Neurocomputing, 2019)

Parallel boosted clustering. - Yazhou Ren 001; Uday Kamath; Carlotta Domeniconi; Zenglin Xu (Neurocomputing, 2019)

Self-paced multi-task clustering. - Yazhou Ren 001; Xiaofan Que; Dezhong Yao 001; Zenglin Xu (Neurocomputing, 2019)

Self-paced and soft-weighted nonnegative matrix factorization for data representation. - Shudong Huang; Peng Zhao; Yazhou Ren 001; Tianrui Li 001; Zenglin Xu (Knowl. Based Syst., 2019)

Low-rank kernel learning for graph-based clustering. - Zhao Kang 001; Liangjian Wen; Wenyu Chen 001; Zenglin Xu (Knowl. Based Syst., 2019)

Auto-weighted multi-view clustering via kernelized graph learning. - Shudong Huang; Zhao Kang 001; Ivor W. Tsang; Zenglin Xu (Pattern Recognit., 2019)

Variational Random Function Model for Network Modeling. - Zenglin Xu; Bin Liu 022; Shandian Zhe; Haoli Bai; Zihan Wang 002; Jennifer Neville (IEEE Trans. Neural Networks Learn. Syst., 2019)

Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis. - Yong Dai 001; Jian Liu; Xiancong Ren; Zenglin Xu (AAAI, 2020)

Large-Scale Multi-View Subspace Clustering in Linear Time. - Zhao Kang 001; Wangtao Zhou; Zhitong Zhao; Junming Shao; Meng Han; Zenglin Xu (AAAI, 2020)

Self-Paced Deep Regression Forests with Consideration on Underrepresented Examples. - Lili Pan 001; Shijie Ai; Yazhou Ren 001; Zenglin Xu (ECCV (30), 2020)

Mutual Information Gradient Estimation for Representation Learning. - Liangjian Wen; Yiji Zhou; Lirong He; Mingyuan Zhou; Zenglin Xu (ICLR, 2020)

Causal Inference for Mixed-Type Data in Additive Noise Models. - Xin Liu; Zenglin Xu; Ping Guo 002 (ICONIP (2), 2020)

Concatenated Tensor Networks for Deep Multi-Task Learning. - Maolin Wang 001; Zeyong Su; Xu Luo 003; Yu Pan 005; Shenggen Zheng; Zenglin Xu (ICONIP (5), 2020)

Learning to Search Efficient DenseNet with Layer-wise Pruning. - Xuanyang Zhang; Hao Liu; Zhanxing Zhu; Zenglin Xu (IJCNN, 2020)

SiNER: A Large Dataset for Sindhi Named Entity Recognition. - Wazir Ali; Junyu Lu; Zenglin Xu (LREC, 2020)

Deep K-Means: A Simple and Effective Method for Data Clustering. - Shudong Huang; Zhao Kang 001; Zenglin Xu (NCAA, 2020)

Multi-Level Multimodal Transformer Network for Multimodal Recipe Comprehension. - Ao Liu 008; Shuai Yuan 018; Chenbin Zhang; Congjian Luo; Yaqing Liao; Kun Bai; Zenglin Xu (SIGIR, 2020)

Improving Contextual Language Models for Response Retrieval in Multi-Turn Conversation. - Junyu Lu; Xiancong Ren; Yazhou Ren 001; Ao Liu 008; Zenglin Xu (SIGIR, 2020)

Read, Attend, and Exclude: Multi-Choice Reading Comprehension by Mimicking Human Reasoning Process. - Chenbin Zhang; Congjian Luo; Junyu Lu; Ao Liu 008; Bing Bai; Kun Bai; Zenglin Xu (SIGIR, 2020)

Combining Multi-Perspective Attention Mechanism With Convolutional Networks for Monaural Speech Enhancement. - Tian Lan 005; Yilan Lyu; Wenzheng Ye; Guoqiang Hui; Zenglin Xu; Qiao Liu 003 (IEEE Access, 2020)

Knowledge Fusion via Joint Tensor and Matrix Factorization. - Zengguang Hao; Yafang Wang; Zining Liu; Gerard de Melo; Zenglin Xu (Cogn. Comput., 2020)

A combination model based on transfer learning for waste classification. - Guang-Li Huang; Jing He 004; Zenglin Xu; Guangyan Huang (Concurr. Comput. Pract. Exp., 2020)

Self-Paced Deep Regression Forests with Consideration on Underrepresented Samples. - Lili Pan 001; Shijie Ai; Yazhou Ren 001; Zenglin Xu (CoRR, 2020)

Discrete Variational Attention Models for Language Generation. - Xianghong Fang; Haoli Bai; Zenglin Xu; Michael R. Lyu; Irwin King (CoRR, 2020)

ReadNet: Towards Accurate ReID with Limited and Noisy Samples. - Yitian Li; Ruini Xue; Mengmeng Zhu; Qing Xu; Zenglin Xu (CoRR, 2020)

Contextualized Code Representation Learning for Commit Message Generation. - Lun Yiu Nie; Cuiyun Gao 001; Zhicong Zhong; Wai Lam; Yang Liu 003; Zenglin Xu (CoRR, 2020)

Heuristic Rank Selection with Progressively Searching Tensor Ring Network. - Nannan Li 003; Yu Pan 005; Yaran Chen; Zixiang Ding; Dongbin Zhao; Zenglin Xu (CoRR, 2020)

A Subword Guided Neural Word Segmentation Model for Sindhi. - Wazir Ali; Jay Kumar; Zenglin Xu; Congjian Luo; Junyu Lu; Junming Shao; Rajesh Kumar 014; Yazhou Ren 001 (CoRR, 2020)

Regularized nonnegative matrix factorization with adaptive local structure learning. - Shudong Huang; Zenglin Xu; Zhao Kang 001; Yazhou Ren 001 (Neurocomputing, 2020)

Two birds with one stone: Transforming and generating facial images with iterative GAN. - Dan Ma 005; Bin Liu 022; Zhao Kang 001; Jiayu Zhou; Jianke Zhu; Zenglin Xu (Neurocomputing, 2020)

Self-paced and auto-weighted multi-view clustering. - Yazhou Ren 001; Shudong Huang; Peng Zhao; Minghao Han; Zenglin Xu (Neurocomputing, 2020)

Auto-weighted multi-view co-clustering with bipartite graphs. - Shudong Huang; Zenglin Xu; Ivor W. Tsang; Zhao Kang 001 (Inf. Sci., 2020)

Multi-graph fusion for multi-view spectral clustering. - Zhao Kang 001; Guoxin Shi; Shudong Huang; Wenyu Chen 001; Xiaorong Pu; Joey Tianyi Zhou; Zenglin Xu (Knowl. Based Syst., 2020)

Deep density-based image clustering. - Yazhou Ren 001; Ni Wang; Mingxia Li; Zenglin Xu (Knowl. Based Syst., 2020)

DART: Domain-Adversarial Residual-Transfer networks for unsupervised cross-domain image classification. - Xianghong Fang; Haoli Bai; Ziyi Guo; Bin Shen 002; Steven C. H. Hoi; Zenglin Xu (Neural Networks, 2020)

Relation-Guided Representation Learning. - Zhao Kang 001; Xiao Lu 004; Jian Liang 002; Kun Bai; Zenglin Xu (Neural Networks, 2020)

Structure learning with similarity preserving. - Zhao Kang 001; Xiao Lu 004; Yiwei Lu; Chong Peng 001; Wenyu Chen 001; Zenglin Xu (Neural Networks, 2020)

Partition level multiview subspace clustering. - Zhao Kang 001; Xinjia Zhao; Chong Peng 001; Hongyuan Zhu; Joey Tianyi Zhou; Xi Peng 001; Wenyu Chen 001; Zenglin Xu (Neural Networks, 2020)

Latent Dirichlet allocation based generative adversarial networks. - Lili Pan 001; Shen Cheng; Jian Liu; Peijun Tang; Bowen Wang; Yazhou Ren 001; Zenglin Xu (Neural Networks, 2020)

Structured pruning of recurrent neural networks through neuron selection. - Liangjian Wen; Xuanyang Zhang; Haoli Bai; Zenglin Xu (Neural Networks, 2020)

Block-term tensor neural networks. - Jinmian Ye; Guangxi Li; Di Chen; Haiqin Yang; Shandian Zhe; Zenglin Xu (Neural Networks, 2020)

Auto-weighted multi-view clustering via deep matrix decomposition. - Shudong Huang; Zhao Kang 001; Zenglin Xu (Pattern Recognit., 2020)

Robust Graph Learning From Noisy Data. - Zhao Kang 001; Haiqi Pan; Steven C. H. Hoi; Zenglin Xu (IEEE Trans. Cybern., 2020)

Multi-document semantic relation extraction for news analytics. - Yongpan Sheng; Zenglin Xu; Yafang Wang; Gerard de Melo (World Wide Web, 2020)

Robustness of Combined sEMG and Ultrasound Modalities Against Muscle Fatigue in Force Estimation. - Jia Zeng; Yu Zhou 013; Yicheng Yang; Zenglin Xu; Hongwei Zhang; Honghai Liu 001 (ICIRA (3), 2021)

Boosting Few-Shot Classification with View-Learnable Contrastive Learning. - Xu Luo 003; Yuxuan Chen; Liangjian Wen; Lili Pan 001; Zenglin Xu (ICME, 2021)

Discrete Auto-regressive Variational Attention Models for Text Modeling. - Xianghong Fang; Haoli Bai; Jian Li 054; Zenglin Xu; Michael R. Lyu; Irwin King (IJCNN, 2021)

Angular Triplet Loss-based Camera Network for ReID. - Yitian Li; Ruini Xue; Mengmeng Zhu; Jing Xu; Zenglin Xu (IJCNN, 2021)

CDD: Multi-view Subspace Clustering via Cross-view Diversity Detection. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001; Quanhui Liu (ACM Multimedia, 2021)

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE. - Qingzhong Ai; Lirong He; Shiyu Liu; Zenglin Xu (NeurIPS, 2021)

Rectifying the Shortcut Learning of Background for Few-Shot Learning. - Xu Luo 003; Longhui Wei; Liangjian Wen; Jinrong Yang; Lingxi Xie; Zenglin Xu; Qi Tian 001 (NeurIPS, 2021)

Creating and Evaluating Resources for Sentiment Analysis in the Low-resource Language: Sindhi. - Wazir Ali; Naveed Ali; Yong Dai 001; Jay Kumar; Saifullah Tumrani; Zenglin Xu (WASSA@EACL, 2021)

Unsupervised Sentiment Analysis by Transferring Multi-source Knowledge. - Yong Dai 001; Jian Liu; Jian Zhang; Hongguang Fu; Zenglin Xu (Cogn. Comput., 2021)

MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance. - Jing Xu; Tszhang Guo; Zenglin Xu; Kun Bai (CoRR, 2021)

Contrastive Disentanglement in Generative Adversarial Networks. - Lili Pan 001; Peijun Tang; Zhiyong Chen; Zenglin Xu (CoRR, 2021)

Partial Differential Equations is All You Need for Generating Neural Architectures - A Theory for Physical Artificial Intelligence Systems. - Ping Guo 002; Kaizhu Huang; Zenglin Xu (CoRR, 2021)

AFINet: Attentive Feature Integration Networks for Image Classification. - Xinglin Pan; Jing Xu; Yu Pan 005; Liangjian Wen; Wenxiang Lin; Kun Bai; Zenglin Xu (CoRR, 2021)

Rectifying the Shortcut Learning of Background: Shared Object Concentration for Few-Shot Image Recognition. - Xu Luo 003; Longhui Wei; Liangjian Wen; Jinrong Yang; Lingxi Xie; Zenglin Xu; Qi Tian 001 (CoRR, 2021)

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE. - Qingzhong Ai; Lirong He; Liangjian Wen; Shiyu Liu; Zenglin Xu (CoRR, 2021)

Kernel Selection for Stein Variational Gradient Descent. - Qingzhong Ai; Shiyu Liu; Zenglin Xu (CoRR, 2021)

FedLab: A Flexible Federated Learning Framework. - Dun Zeng; Siqi Liang 001; Xiangjing Hu; Zenglin Xu (CoRR, 2021)

Graph Partner Neural Networks for Semi-Supervised Learning on Graphs. - Langzhang Liang; Cuiyun Gao 001; Shiyi Chen; Shishi Duan; Yu Pan 005; Junjin Zheng; Lei Wang; Zenglin Xu (CoRR, 2021)

Self-Paced Deep Regression Forests with Consideration on Ranking Fairness. - Lili Pan 001; Mingming Meng; Yazhou Ren 001; Yali Zheng; Zenglin Xu (CoRR, 2021)

Exploring Category-correlated Feature for Few-shot Image Classification. - Jing Xu; Xinglin Pan; Xu Luo 003; Wenjie Pei; Zenglin Xu (CoRR, 2021)

Machine learning based early mortality prediction in the emergency department. - Cong Li; Zhuo Zhang 007; Yazhou Ren 001; Hu Nie; Yuqing Lei; Hang Qiu 002; Zenglin Xu; Xiaorong Pu (Int. J. Medical Informatics, 2021)

CoreGen: Contextualized Code Representation Learning for Commit Message Generation. - Lun Yiu Nie; Cuiyun Gao 001; Zhicong Zhong; Wai Lam; Yang Liu 003; Zenglin Xu (Neurocomputing, 2021)

MultiFace: A generic training mechanism for boosting face recognition performance. - Jing Xu; Tszhang Guo; Yong Xu 001; Zenglin Xu; Kun Bai (Neurocomputing, 2021)

Domain adaptation with feature and label adversarial networks. - Peng Zhao; Wenhua Zang; Bin Liu 022; Zhao Kang 001; Kun Bai; Kaizhu Huang; Zenglin Xu (Neurocomputing, 2021)

Multi-view subspace clustering via partition fusion. - Juncheng Lv; Zhao Kang 001; Boyu Wang 004; Luping Ji; Zenglin Xu (Inf. Sci., 2021)

Deep embedded multi-view clustering with collaborative training. - Jie Xu 044; Yazhou Ren 001; Guofeng Li; Lili Pan 001; Ce Zhu; Zenglin Xu (Inf. Sci., 2021)

Gradient estimation of information measures in deep learning. - Liangjian Wen; Haoli Bai; Lirong He; Yiji Zhou; Mingyuan Zhou; Zenglin Xu (Knowl. Based Syst., 2021)

Byzantine Resistant Secure Blockchained Federated Learning at the Edge. - Zonghang Li; Hongfang Yu; Tianyao Zhou; Long Luo; Mochan Fan; Zenglin Xu; Gang Sun 001 (IEEE Netw., 2021)

CRaDLe: Deep code retrieval based on semantic Dependency Learning. - Wenchao Gu; Zongjie Li; Cuiyun Gao 001; Chaozheng Wang; Hongyu Zhang 002; Zenglin Xu; Michael R. Lyu (Neural Networks, 2021)

Robust deep k-means: An effective and simple method for data clustering. - Shudong Huang; Zhao Kang 001; Zenglin Xu; Quanhui Liu (Pattern Recognit., 2021)

Structured graph learning for clustering and semi-supervised classification. - Zhao Kang 001; Chong Peng 001; Qiang Cheng 001; Xinwang Liu 002; Xi Peng 001; Zenglin Xu; Ling Tian (Pattern Recognit., 2021)

Pseudo-Supervised Deep Subspace Clustering. - Juncheng Lv; Zhao Kang 001; Xiao Lu 004; Zenglin Xu (IEEE Trans. Image Process., 2021)

Multi-View Clustering on Topological Manifold. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001; Quanhui Liu (AAAI, 2022)

Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training. - Shenglai Zeng; Zonghang Li; Hongfang Yu; Yihong He; Zenglin Xu; Dusit Niyato; Han Yu 001 (DASFAA (2), 2022)

Leveraging Only the Category Name for Aspect Detection through Prompt-based Constrained Clustering. - Yazheng Li; Pengyun Wang; Yasheng Wang; Yong Dai 001; Yadao Wang; Lujia Pan; Zenglin Xu (EMNLP (Findings), 2022)

Learning to Generate Question by Asking Question: A Primal-Dual Approach with Uncommon Word Generation. - Qifan Wang 001; Li Yang; Xiaojun Quan; Fuli Feng; Dongfang Liu; Zenglin Xu; Sinong Wang; Hao Ma 001 (EMNLP, 2022)

SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction. - Qifan Wang 001; Li Yang; Jingang Wang; Jitin Krishnan; Bo Dai 001; Sinong Wang; Zenglin Xu; Madian Khabsa; Hao Ma 001 (EMNLP (Findings), 2022)

Federated Model Decomposition with Private Vocabulary for Text Classification. - Zhuo Zhang 007; Xiangjing Hu; Lizhen Qu; Qifan Wang 001; Zenglin Xu (EMNLP, 2022)

Semantically Proportional Patchmix for Few-Shot Learning. - Jingquan Wang; Jing Xu; Yu Pan 005; Zenglin Xu (ICASSP, 2022)

Field-aware Variational Autoencoders for Billion-scale User Representation Learning. - Ge Fan; Chaoyun Zhang; Junyang Chen 001; Baopu Li; Zenglin Xu; Yingjie Li; Luyu Peng; Zhiguo Gong (ICDE, 2022)

A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks. - Yu Pan 005; Zeyong Su; Ao Liu 008; Jingquan Wang; Nannan Li 001; Zenglin Xu (ICML, 2022)

Channel Importance Matters in Few-Shot Image Classification. - Xu Luo 003; Jing Xu; Zenglin Xu (ICML, 2022)

Contrastive Multi-view Hyperbolic Hierarchical Clustering. - Fangfei Lin; Bing Bai; Kun Bai; Yazhou Ren 001; Peng Zhao; Zenglin Xu (IJCAI, 2022)

ACE: A Coarse-to-Fine Learning Framework for Reliable Representation Learning Against Label Noise. - Chenbin Zhang; Xiangli Yang; Jian Liang 002; Bing Bai; Kun Bai; Irwin King; Zenglin Xu (IJCNN, 2022)

Learning Smooth Representation for Multi-view Subspace Clustering. - Shudong Huang; Yixi Liu; Yazhou Ren 001; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (ACM Multimedia, 2022)

Multi-view Subspace Clustering on Topological Manifold. - Shudong Huang; Hongjie Wu; Yazhou Ren 001; Ivor W. Tsang; Zenglin Xu; Wentao Feng; Jiancheng Lv 001 (NeurIPS, 2022)

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid. - Jing Xu; Xu Luo 003; Xinglin Pan; Yanan Li; Wenjie Pei; Zenglin Xu (NeurIPS, 2022)

Source Code Summarization with Structural Relative Position Guided Transformer. - Zi Gong; Cuiyun Gao 001; Yasheng Wang; Wenchao Gu; Yun Peng 003; Zenglin Xu (SANER, 2022)

MarkBERT: Marking Word Boundaries Improves Chinese BERT. - Linyang Li; Yong Dai 001; Duyu Tang; Xipeng Qiu; Zenglin Xu; Shuming Shi 001 (CoRR, 2022)

Aggregating Gradients in Encoded Domain for Federated Learning. - Dun Zeng; Shiyu Liu; Zenglin Xu (CoRR, 2022)

ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization. - Langzhang Liang; Zenglin Xu; Zixing Song; Irwin King; Jieping Ye (CoRR, 2022)

A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities. - Yaoxian Li; Shiyi Qi; Cuiyun Gao 001; Yun Peng 003; David Lo 001; Zenglin Xu; Michael R. Lyu (CoRR, 2022)

Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling. - Yuanhang Yang; Shiyi Qi; Cuiyun Gao 001; Zenglin Xu; Yulan He 001; Qifan Wang 001; Chuanyi Liu (CoRR, 2022)

MultiCoder: Multi-Programming-Lingual Pre-Training for Low-Resource Code Completion. - Zi Gong; Yinpeng Guo; Pingyi Zhou; Cuiyun Gao 001; Yasheng Wang; Zenglin Xu (CoRR, 2022)

When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods. - Zhuo Zhang 007; Yuanhang Yang; Yong Dai 001; Lizhen Qu; Zenglin Xu (CoRR, 2022)

TedNet: A Pytorch toolkit for tensor decomposition networks. - Yu Pan 005; Maolin Wang 001; Zenglin Xu (Neurocomputing, 2022)

Non-uniform Nyström approximation for sparse kernel regression: Theoretical analysis and experimental evaluation. - Qian Zhang; Wei Shi; Steven Hoi; Zenglin Xu (Neurocomputing, 2022)

Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT. - Zonghang Li; Yihong He; Hongfang Yu; Jiawen Kang 001; Xiaoping Li 002; Zenglin Xu; Dusit Niyato (IEEE Internet Things J., 2022)

Graph Fusion Network for Text Classification. - Yong Dai 001; Linjun Shou; Ming Gong 001; Xiaolin Xia; Zhao Kang 001; Zenglin Xu; Daxin Jiang (Knowl. Based Syst., 2022)

Spaks: Self-paced multiple kernel subspace clustering with feature smoothing regularization. - Qian Zhang; Zhao Kang 001; Zenglin Xu; Shudong Huang; Hongguang Fu (Knowl. Based Syst., 2022)

Multiple partitions alignment via spectral rotation. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (Mach. Learn., 2022)

Re-thinking model robustness from stability: a new insight to defend adversarial examples. - Shufei Zhang; Kaizhu Huang; Zenglin Xu (Mach. Learn., 2022)

AFINet: Attentive Feature Integration Networks for image classification. - Xinglin Pan; Jing Xu; Yu Pan 005; Liangjian Wen; Wenxiang Lin; Kun Bai; Hongguang Fu; Zenglin Xu (Neural Networks, 2022)

Efficient federated multi-view learning. - Shudong Huang; Wei Shi; Zenglin Xu; Ivor W. Tsang; Jiancheng Lv 001 (Pattern Recognit., 2022)

Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-View Clustering. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2022)

Improved Inference for Imputation-Based Semisupervised Learning Under Misspecified Setting. - Shaogao Lv; Linsen Wei; Qian Zhang; Bin Liu 022; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2022)

ESync: Accelerating Intra-Domain Federated Learning in Heterogeneous Data Centers. - Zonghang Li; Huaman Zhou; Tianyao Zhou; Hongfang Yu; Zenglin Xu; Gang Sun 001 (IEEE Trans. Serv. Comput., 2022)

Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering. - Zongmo Huang; Yazhou Ren 001; Xiaorong Pu; Shudong Huang; Zenglin Xu; Lifang He 001 (AAAI, 2023)

MUSTIE: Multimodal Structural Transformer for Web Information Extraction. - Qifan Wang 001; Jingang Wang; Xiaojun Quan; Fuli Feng; Zenglin Xu; Shaoliang Nie; Sinong Wang; Madian Khabsa; Hamed Firooz; Dongfang Liu (ACL (1), 2023)

MixPAVE: Mix-Prompt Tuning for Few-shot Product Attribute Value Extraction. - Li Yang; Qifan Wang 001; Jingang Wang; Xiaojun Quan; Fuli Feng; Yu Chen 022; Madian Khabsa; Sinong Wang; Zenglin Xu; Dongfang Liu (ACL (Findings), 2023)

FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP. - Zhuo Zhang 007; Xiangjing Hu; Jingyuan Zhang; Yating Zhang; Hui Wang 013; Lizhen Qu; Zenglin Xu (ACL (1), 2023)

FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models. - Zhuo Zhang 007; Yuanhang Yang; Yong Dai 001; Qifan Wang 001; Yue Yu 001; Lizhen Qu; Zenglin Xu (ACL (Findings), 2023)

Generative Oversampling for Imbalanced Data via Majority-Guided VAE. - Qingzhong Ai; Pengyun Wang; Lirong He; Liangjian Wen; Lujia Pan; Zenglin Xu (AISTATS, 2023)

ViLPAct: A Benchmark for Compositional Generalization on Multimodal Human Activities. - Terry Yue Zhuo; Yaqing Liao; Yuecheng Lei; Lizhen Qu; Gerard de Melo; Xiaojun Chang; Yazhou Ren 001; Zenglin Xu (EACL (Findings), 2023)

APrompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models. - Qifan Wang 001; Yuning Mao; Jingang Wang; Hanchao Yu; Shaoliang Nie; Sinong Wang; Fuli Feng; Lifu Huang; Xiaojun Quan; Zenglin Xu; Dongfang Liu (EMNLP, 2023)

Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling. - Yuanhang Yang; Shiyi Qi; Chuanyi Liu; Qifan Wang 001; Cuiyun Gao 001; Zenglin Xu (EMNLP, 2023)

Multi-Task Transformer with Relation-Attention and Type-Attention for Named Entity Recognition. - Ying Mo; Hongyin Tang; Jiahao Liu; Qifan Wang 001; Zenglin Xu; Jingang Wang; Wei Wu 014; Zhoujun Li 001 (ICASSP, 2023)

MHCN: A Hyperbolic Neural Network Model for Multi-view Hierarchical Clustering. - Fangfei Lin; Bing Bai; Yiwen Guo; Hao Chen 003; Yazhou Ren 001; Zenglin Xu (ICCV, 2023)

Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization. - Maolin Wang 001; Dun Zeng; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001 (ICDM, 2023)

Quantized SGD in Federated Learning: Communication, Optimization and Generalization. - Shiyu Liu; Linsen Wei; Shaogao Lv; Zenglin Xu (ICONIP (9), 2023)

Generalized Category Discovery with Clustering Assignment Consistency. - Xiangli Yang; Xinglin Pan; Irwin King; Zenglin Xu (ICONIP (5), 2023)

Contrastive Kernel Subspace Clustering. - Qian Zhang; Zhao Kang 001; Zenglin Xu; Hongguang Fu (ICONIP (5), 2023)

SMARTformer: Semi-Autoregressive Transformer with Efficient Integrated Window Attention for Long Time Series Forecasting. - Yiduo Li; Shiyi Qi; Zhe Li; Zhongwen Rao; Lujia Pan; Zenglin Xu (IJCAI, 2023)

Prompt Learns Prompt: Exploring Knowledge-Aware Generative Prompt Collaboration For Video Captioning. - Liqi Yan; Cheng Han 001; Zenglin Xu; Dongfang Liu; Qifan Wang 001 (IJCAI, 2023)

Flexible Contribution Estimation Methods for Horizontal Federated Learning. - Xiangjing Hu; Congjian Luo; Dun Zeng; Zenglin Xu; Ping Guo 002; Irwin King (IJCNN, 2023)

Reusing Pretrained Models by Multi-linear Operators for Efficient Training. - Yu Pan 005; Ye Yuan 016; Yichun Yin; Zenglin Xu; Lifeng Shang; Xin Jiang 002; Qun Liu 001 (NeurIPS, 2023)

Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily. - Langzhang Liang; Xiangjing Hu; Zenglin Xu; Zixing Song; Irwin King (NeurIPS, 2023)

Practical privacy-preserving Gaussian process regression via secret sharing. - Jinglong Luo; Yehong Zhang; Jiaqi Zhang; Shuang Qin; Hui Wang 013; Yue Yu 001; Zenglin Xu (UAI, 2023)

1st Workshop on Federated Learning Technologies. - Mirko Polato; Roberto Esposito; Walter Riviera; Zenglin Xu; Irwin King (WWW (Companion Volume), 2023)

A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy. - Yifei Zhang; Dun Zeng; Jinglong Luo; Zenglin Xu; Irwin King (WWW (Companion Volume), 2023)

Ti-MAE: Self-Supervised Masked Time Series Autoencoders. - Zhe Li; Zhongwen Rao; Lujia Pan; Pengyun Wang; Zenglin Xu (CoRR, 2023)

MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing. - Zhe Li; Zhongwen Rao; Lujia Pan; Zenglin Xu (CoRR, 2023)

Tensor Networks Meet Neural Networks: A Survey. - Maolin Wang 001; Yu Pan 005; Xiangli Yang; Guangxi Li; Zenglin Xu (CoRR, 2023)

Stochastic Clustered Federated Learning. - Dun Zeng; Xiangjing Hu; Shiyu Liu; Yue Yu 001; Qifan Wang 001; Zenglin Xu (CoRR, 2023)

BadCS: A Backdoor Attack Framework for Code search. - Shiyi Qi; Yuanhang Yang; Shuzheng Gao; Cuiyun Gao 001; Zenglin Xu (CoRR, 2023)

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping. - Zhe Li; Shiyi Qi; Yiduo Li; Zenglin Xu (CoRR, 2023)

Tensorized Hypergraph Neural Networks. - Maolin Wang 001; Yaoming Zhen; Yu Pan 005; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001 (CoRR, 2023)

FedNoisy: Federated Noisy Label Learning Benchmark. - Siqi Liang 001; Jintao Huang; Dun Zeng; Junyuan Hong; Jiayu Zhou; Zenglin Xu (CoRR, 2023)

Personalized Federated Learning via Amortized Bayesian Meta-Learning. - Shiyu Liu; Shaogao Lv; Dun Zeng; Zenglin Xu; Hui Wang 013; Yue Yu 001 (CoRR, 2023)

Exploring Federated Optimization by Reducing Variance of Adaptive Unbiased Client Sampling. - Dun Zeng; Zenglin Xu; Yu Pan 005; Qifan Wang 001; Xiaoying Tang 002 (CoRR, 2023)

Tackling Hybrid Heterogeneity on Federated Optimization via Gradient Diversity Maximization. - Dun Zeng; Zenglin Xu; Yu Pan 005; Qifan Wang 001; Xiaoying Tang 002 (CoRR, 2023)

Less is More: On the Feature Redundancy of Pretrained Models When Transferring to Few-shot Tasks. - Xu Luo 003; Difan Zou; Lianli Gao; Zenglin Xu; Jingkuan Song (CoRR, 2023)

Federated Generalization via Information-Theoretic Distribution Diversification. - Zheshun Wu; Zenglin Xu; Dun Zeng; Qifan Wang 001 (CoRR, 2023)

On Diversified Preferences of Large Language Model Alignment. - Dun Zeng; Yong Dai 001; Pengyu Cheng; Tianhao Hu; Wanshun Chen; Nan Du; Zenglin Xu (CoRR, 2023)

Edge enhancement improves adversarial robustness in image classification. - Lirong He; Qingzhong Ai; Yuqing Lei; Lili Pan 001; Yazhou Ren 001; Zenglin Xu (Neurocomputing, 2023)

FedLab: A Flexible Federated Learning Framework. - Dun Zeng; Siqi Liang 001; Xiangjing Hu; Hui Wang 013; Zenglin Xu (J. Mach. Learn. Res., 2023)

Learning to generate complex question with intent prediction from long passage. - Youcheng Pan; Baotian Hu; Shiyue Wang; Xiaolong Wang 001; Qingcai Chen; Zenglin Xu; Min Zhang 005 (Appl. Intell., 2023)

Stein Variational Gradient Descent with Multiple Kernels. - Qingzhong Ai; Shiyu Liu; Lirong He; Zenglin Xu (Cogn. Comput., 2023)

Latent Representation Guided Multi-View Clustering. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2023)

Multi-View Subspace Clustering by Joint Measuring of Consistency and Diversity. - Shudong Huang; Yixi Liu; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2023)

A Survey on Deep Semi-Supervised Learning. - Xiangli Yang; Zixing Song; Irwin King; Zenglin Xu (IEEE Trans. Knowl. Data Eng., 2023)

Boosting adversarial robustness via self-paced adversarial training. - Lirong He; Qingzhong Ai; Xincheng Yang; Yazhou Ren 001; Qifan Wang 001; Zenglin Xu (Neural Networks, 2023)

Single image denoising with a feature-enhanced network. - Ruibin Zhuge; Jinghua Wang; Zenglin Xu; Yong Xu 001 (Neural Networks, 2023)

Graph-Based Semi-Supervised Learning: A Comprehensive Review. - Zixing Song; Xiangli Yang; Zenglin Xu; Irwin King (IEEE Trans. Neural Networks Learn. Syst., 2023)

RegNet: Self-Regulated Network for Image Classification. - Jing Xu; Yu Pan 005; Xinglin Pan; Steven C. H. Hoi; Zhang Yi 001; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2023)

Preparing Lessons for Progressive Training on Language Models. - Yu Pan 005; Ye Yuan 016; Yichun Yin; Jiaxin Shi; Zenglin Xu; Ming Zhang 004; Lifeng Shang; Xin Jiang 002; Qun Liu 001 (AAAI, 2024)

Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks. - Junjie Chen 004; Jiahao Li; Chen Song; Bin Li; Qingcai Chen; Hongchang Gao; Wendy Hui Wang; Zenglin Xu; Xinghua Shi (AAAI, 2024)

OctOcc: High-Resolution 3D Occupancy Prediction with Octree. - Wenzhe Ouyang; Xiaolin Song; Bailan Feng; Zenglin Xu (AAAI, 2024)

SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC. - Jinglong Luo; Yehong Zhang; Zhuo Zhang 007; Jiaqi Zhang; Xin Mu; Hui Wang 013; Yue Yu 001; Zenglin Xu (ACL (Findings), 2024)

XMoE: Sparse Models with Fine-grained and Adaptive Expert Selection. - Yuanhang Yang; Shiyi Qi; Wenchao Gu; Chaozheng Wang; Cuiyun Gao 001; Zenglin Xu (ACL (Findings), 2024)

Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack. - Guanzhong Chen; Zhenghan Qin; Mingxin Yang; Yajie Zhou; Tao Fan 002; Tianyu Du; Zenglin Xu (CCS, 2024)

Revisiting Data Reconstruction Attacks on Real-world Dataset for Federated Natural Language Understanding. - Zhuo Zhang 007; Jintao Huang; Xiangjing Hu; Jingyuan Zhang; Yating Zhang; Hui Wang 013; Yue Yu 001; Qifan Wang 001; Lizhen Qu; Zenglin Xu (LREC/COLING, 2024)

M²PT: Multimodal Prompt Tuning for Zero-shot Instruction Learning. - Taowen Wang; Yiyang Liu 003; James Liang; Junhan Zhao; Yiming Cui 002; Yuning Mao; Shaoliang Nie; Jiahao Liu; Fuli Feng; Zenglin Xu; Cheng Han 001; Lifu Huang; et al. (EMNLP, 2024)

EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction. - Li Yang; Qifan Wang 001; Jianfeng Chi; Jiahao Liu; Jingang Wang; Fuli Feng; Zenglin Xu; Yi Fang 008; Lifu Huang; Dongfang Liu (EMNLP (Findings), 2024)

On Diversified Preferences of Large Language Model Alignment. - Dun Zeng; Yong Dai 001; Pengyu Cheng; Longyue Wang; Tianhao Hu; Wanshun Chen; Nan Du; Zenglin Xu (EMNLP (Findings), 2024)

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs. - Langzhang Liang; Sunwoo Kim 006; Kijung Shin; Zenglin Xu; Shirui Pan; Yuan Qi 001 (ICML, 2024)

Combining Explicit Priors and Set Attention Driven Implicit Priors for Demonstration-Guided Reinforcement Learning. - Shujiong Tang; Irwin King; Zenglin Xu (ICONIP (4), 2024)

Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy. - Shiyu Liu; Wei Shi; Zenglin Xu; Shaogao Lv; Yehong Zhang; Hui Wang 013 (IJCAI, 2024)

A Systematic Survey on Federated Semi-supervised Learning. - Zixing Song; Xiangli Yang; Yifei Zhang; Xinyu Fu 004; Zenglin Xu; Irwin King (IJCAI, 2024)

Federated Learning for Vehicle Trajectory Prediction: Methodology and Benchmark Study. - Hongye Wang; Ruonan Li; Zenglin Xu; Jinlong Li; Irwin King; Jie Liu 001 (IJCNN, 2024)

FedLFC: Towards Efficient Federated Multilingual Modeling with LoRA-based Language Family Clustering. - Zhihan Guo; Yifei Zhang; Zhuo Zhang 007; Zenglin Xu; Irwin King (NAACL-HLT (Findings), 2024)

On the Necessity of Collaboration for Online Model Selection with Decentralized Data. - Junfan Li; Zheshun Wu; Zenglin Xu; Irwin King (NeurIPS, 2024)

Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approach. - Bin Hu; Chenyang Zhao; Pu Zhang; Zihao Zhou; Yuanhang Yang; Zenglin Xu; Bin Liu 022 (RLJ, 2024)

Tensorized Hypergraph Neural Networks. - Maolin Wang 001; Yaoming Zhen; Yu Pan 005; Yao Zhao; Chenyi Zhuang; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001 (SDM, 2024)

FedHLT: Efficient Federated Low-Rank Adaption with Hierarchical Language Tree for Multilingual Modeling. - Zhihan Guo; Yifei Zhang; Zhuo Zhang 007; Zenglin Xu; Irwin King (WWW (Companion Volume), 2024)

FL@FM-TheWebConf'24: International Workshop on Federated Foundation Models for the Web. - Irwin King; Guodong Long; Zenglin Xu; Han Yu 001 (WWW (Companion Volume), 2024)

Enhancing Sindhi Word Segmentation Using Subword Representation Learning and Position-Aware Self-Attention. - Wazir Ali; Jay Kumar; Saifullah Tumani; Redhwan Nour; Adeeb Noor; Zenglin Xu (IEEE Access, 2024)

A Survey on Scheduling Techniques in Computing and Network Convergence. - Shujiong Tang; Yue Yu 001; Hui Wang 073; Guiliang Wang; Wuhui Chen; Zenglin Xu; Song Guo 001; Wen Gao 001 (IEEE Commun. Surv. Tutorials, 2024)

SecFormer: Towards Fast and Accurate Privacy-Preserving Inference for Large Language Models. - Jinglong Luo; Yehong Zhang; Jiaqi Zhang; Xin Mu; Hui Wang 013; Yue Yu 001; Zenglin Xu (CoRR, 2024)

Cumulative Distribution Function based General Temporal Point Processes. - Maolin Wang 001; Yu Pan 005; Zenglin Xu; Ruocheng Guo; Xiangyu Zhao 001; Wanyu Wang; Yiqi Wang 001; Zitao Liu 001; Langming Liu (CoRR, 2024)

PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations. - Shiyi Qi; Zenglin Xu; Yiduo Li; Liangjian Wen; Qingsong Wen; Qifan Wang 001; Yuan Qi 001 (CoRR, 2024)

Enhancing Multivariate Time Series Forecasting with Mutual Information-driven Cross-Variable and Temporal Modeling. - Shiyi Qi; Liangjian Wen; Yiduo Li; Yuanhang Yang; Zhe Li; Zhongwen Rao; Lujia Pan; Zenglin Xu (CoRR, 2024)

FedPIT: Towards Privacy-preserving and Few-shot Federated Instruction Tuning. - Zhuo Zhang 007; Jingyuan Zhang; Jintao Huang; Lizhen Qu; Hongzhi Zhang; Zenglin Xu (CoRR, 2024)

Enhancing Efficiency in Sparse Models with Sparser Selection. - Yuanhang Yang; Shiyi Qi; Wenchao Gu; Chaozheng Wang; Cuiyun Gao 001; Zenglin Xu (CoRR, 2024)

A Survey on Diffusion Models for Time Series and Spatio-Temporal Data. - Yiyuan Yang; Ming Jin 005; Haomin Wen; Chaoli Zhang 001; Yuxuan Liang; Lintao Ma; Yi Wang 022; Chenghao Liu; Bin Yang 002; Zenglin Xu; Jiang Bian 001; Shirui Pan; et al. (CoRR, 2024)

Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives. - Yiyuan Yang; Zheshun Wu; Yong Chu; Zhenghua Chen; Zenglin Xu; Qingsong Wen (CoRR, 2024)

Time Series Analysis for Education: Methods, Applications, and Future Directions. - Shengzhong Mao; Chaoli Zhang 001; Yichi Song; Jindong Wang 001; Xiao-Jun Zeng; Zenglin Xu; Qingsong Wen (CoRR, 2024)

Online Optimization for Learning to Communicate over Time-Correlated Channels. - Zheshun Wu; Junfan Li; Zenglin Xu; Sumei Sun; Jie Liu 001 (CoRR, 2024)

Can we only use guideline instead of shot in prompt? - Jiaxiang Chen; Song Wang; Zhucong Li; Wayne Xiong; Lizhen Qu; Zenglin Xu; Yuan Qi 001 (CoRR, 2024)

M2PT: Multimodal Prompt Tuning for Zero-shot Instruction Learning. - Taowen Wang; Yiyang Liu 003; James Chenhao Liang; Junhan Zhao; Yiming Cui 002; Yuning Mao; Shaoliang Nie; Jiahao Liu; Fuli Feng; Zenglin Xu; Cheng Han 001; Lifu Huang; et al. (CoRR, 2024)

TimeCNN: Refining Cross-Variable Interaction on Time Point for Time Series Forecasting. - Ao Hu; Dongkai Wang; Yong Dai 001; Shiyi Qi; Liangjian Wen; Jun Wang; Zhi Chen; Xun Zhou 001; Zenglin Xu; Jiang Duan (CoRR, 2024)

MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning. - Ziliang Gan; Yu Lu; Dong Zhang; Haohan Li; Che Liu; Jian Liu; Ji Liu; Haipang Wu; Chaoyou Fu; Zenglin Xu; Rongjunchen Zhang; Yong Dai 001 (CoRR, 2024)

FedCVD: The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data. - Yukun Zhang; Guanzhong Chen; Zenglin Xu; Jianyong Wang 001; Dun Zeng; Junfan Li; Jinghua Wang; Yuan Qi 001; Irwin King (CoRR, 2024)

Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization. - Dun Zeng; Zheshun Wu; Shiyu Liu; Yu Pan 005; Xiaoying Tang 002; Zenglin Xu (CoRR, 2024)

Predicting intubation for intensive care units patients: A deep learning approach to improve patient management. - Ruixi Li; Zenglin Xu; Jing Xu; Xinglin Pan; Hong Wu; Xiaobo Huang; Mengling Feng (Int. J. Medical Informatics, 2024)

Efficient privacy-preserving Gaussian process via secure multi-party computation. - Shiyu Liu; Jinglong Luo; Yehong Zhang; Hui Wang 013; Yue Yu 001; Zenglin Xu (J. Syst. Archit., 2024)

CUPID: Improving Battle Fairness and Position Satisfaction in Online MOBA Games with a Re-matchmaking System. - Ge Fan; Chaoyun Zhang; Kai Wang; Yingjie Li; Junyang Chen 001; Zenglin Xu (Proc. ACM Hum. Comput. Interact., 2024)

MixingMask: A contour-aware approach for joint object detection and instance segmentation. - Wenzhe Ouyang; Zenglin Xu; Jing Xu; Qifan Wang 001; Yong Xu 001 (Pattern Recognit., 2024)

Information-Theoretic Generalization Analysis for Topology-Aware Heterogeneous Federated Edge Learning Over Noisy Channels. - Zheshun Wu; Zenglin Xu; Hongfang Yu; Jie Liu 001 (IEEE Signal Process. Lett., 2024)

Multi-Task Multi-Attention Transformer for Generative Named Entity Recognition. - Ying Mo; Jiahao Liu; Hongyin Tang; Qifan Wang 001; Zenglin Xu; Jingang Wang; Xiaojun Quan; Wei Wu 014; Zhoujun Li 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

TopicAns: Topic-informed Architecture for Answer Recommendation on Technical Q&A Site. - Yuanhang Yang; Wei He 024; Cuiyun Gao 001; Zenglin Xu; Xin Xia 001; Chuanyi Liu (ACM Trans. Softw. Eng. Methodol., 2024)

Adaptive asynchronous federated learning. - Renhao Lu; Weizhe Zhang; Qiong Li 001; Hui He; Xiaoxiong Zhong; Hongwei Yang; Desheng Wang 002; Zenglin Xu; Mamoun Alazab (Future Gener. Comput. Syst., 2024)

CGDD: Multiview Graph Clustering via Cross-Graph Diversity Detection. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Tackling Long-Tailed Distribution Issue in Graph Neural Networks via Normalization. - Langzhang Liang; Zenglin Xu; Zixing Song; Irwin King; Yuan Qi 001; Jieping Ye (IEEE Trans. Knowl. Data Eng., 2024)

Label-Aware Distribution Calibration for Long-Tailed Classification. - Chaozheng Wang; Shuzheng Gao; Pengyun Wang; Cuiyun Gao 001; Wenjie Pei; Lujia Pan; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2024)

Topology Learning for Heterogeneous Decentralized Federated Learning Over Unreliable D2D Networks. - Zheshun Wu; Zenglin Xu; Dun Zeng; Junfan Li; Jie Liu 001 (IEEE Trans. Veh. Technol., 2024)

MVEB: Self-Supervised Learning With Multi-View Entropy Bottleneck. - Liangjian Wen; Xiasi Wang; Jianzhuang Liu; Zenglin Xu (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Survey of Trustworthy Federated Learning: Issues, Solutions, and Challenges. - Yifei Zhang; Dun Zeng; Jinglong Luo; Xinyu Fu 004; Guanzhong Chen; Zenglin Xu; Irwin King (ACM Trans. Intell. Syst. Technol., 2024)

Euclidean Distance is Not Your Swiss Army Knife. - Yuze Tan; Yixi Liu; Hongjie Wu; Shudong Huang; Zenglin Xu; Ivor W. Tsang; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2024)

GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models Through Statistically-Guided Geo-Prototyping. - Bang An 002; Xun Zhou 001; Zirui Zhou; Ronilo J. Ragodos; Zenglin Xu; Jun Luo 007 (AAAI, 2025)

CENTAUR: Bridging the Impossible Trinity of Privacy, Efficiency, and Performance in Privacy-Preserving Transformer Inference. - Jinglong Luo; Guanzhong Chen; Yehong Zhang; Shiyu Liu; Hui Wang 013; Yue Yu 001; Xun Zhou 001; Yuan Qi 001; Zenglin Xu (ACL (1), 2025)

On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond. - Dun Zeng; Zenglin Xu; Shiyu Liu; Yu Pan 005; Qifan Wang 001; Xiaoying Tang 002 (AISTATS, 2025)

A Polynomial-time Algorithm for Online Sparse Linear Regression with Improved Regret Bound under Weaker Conditions. - Junfan Li; Shizhong Liao; Zenglin Xu; Liqiang Nie (COLT, 2025)

IDInit: A Universal and Stable Initialization Method for Neural Network Training. - Yu Pan 005; Chaozheng Wang; Zekai Wu; Qifan Wang 001; Min Zhang 014; Zenglin Xu (ICLR, 2025)

Preference-Strength-Aware Self-Improving Alignment with Generative Preference Models. - Yuanzhao Zhai; Zhuo Zhang 007; Cheng Yang 004; Kele Xu; Yue Yu 001; Wei Li; Hui Wang 030; Zenglin Xu; Dawei Feng; Bo Ding; Huaimin Wang (SIGIR, 2025)

FL@FM-TheWebConf'25: International Workshop on Federated Foundation Models for the Web 2025. - Irwin King; Guodong Long; Zenglin Xu; Yifei Zhang; Han Yu 001 (WWW (Companion Volume), 2025)

From continuous pre-training to alignment: A comprehensive toolkit for large language models in federated learning. - Zhuo Zhang 007; Yukun Zhang; Guanzhong Chen; Lizhen Qu; Xun Zhou 001; Hui Wang 013; Zenglin Xu (Neurocomputing, 2025)

StoCFL: A stochastically clustered federated learning framework for Non-IID data with dynamic client participation. - Dun Zeng; Xiangjing Hu; Shiyu Liu; Yue Yu 001; Qifan Wang 001; Zenglin Xu (Neural Networks, 2025)

PlanePDM: Boundary-aware 3D planar recovery by using parallel dilated mask head. - Wenzhe Ouyang; Zenglin Xu; Qianying Zhu; Bin Shen 002; Yong Xu 001 (Pattern Recognit., 2025)

Enhanced Federated Optimization: Adaptive Unbiased Client Sampling with Reduced Variance. - Dun Zeng; Zenglin Xu; Yu Pan 005; Xu Luo 003; Qifan Wang 001; Xiaoying Tang 002 (Trans. Mach. Learn. Res., 2025)

Position: LLMs Can be Good Tutors in Foreign Language Education. - Jingheng Ye; Shen Wang 005; Deqing Zou; Yibo Yan; Kun Wang 042; Hai-Tao Zheng 002; Zenglin Xu; Irwin King; Philip S. Yu; Qingsong Wen (CoRR, 2025)

LinkOcc: 3D Semantic Occupancy Prediction With Temporal Association. - Wenzhe Ouyang; Zenglin Xu; Bin Shen 002; Jinghua Wang; Yong Xu 001 (IEEE Trans. Circuits Syst. Video Technol., 2025)

CORE: CORrelation-Guided Feature Enhancement for Few-Shot Image Classification. - Jing Xu; Xinglin Pan; Jingquan Wang; Wenjie Pei; Qing Liao 001; Zenglin Xu (IEEE Trans. Neural Networks Learn. Syst., 2025)

Understanding the Robustness of Transformer-Based Code Intelligence via Code Transformation: Challenges and Opportunities. - Yaoxian Li; Shiyi Qi; Cuiyun Gao 001; Yun Peng 003; David Lo 001; Michael R. Lyu; Zenglin Xu (IEEE Trans. Software Eng., 2025)

Nexus-O: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision. - Che Liu; Yingji Zhang; Dong Zhang; Weijie Zhang; Chenggong Gong; Haohan Li; Yu Lu; Shilin Zhou 002; Yue Lu; Ziliang Gan; Ziao Wang; Junwei Liao; et al. (CoRR, 2025)

Heterogeneous Group-Based Reinforcement Learning for LLM-based Multi-Agent Systems. - Guanzhong Chen; Shaoxiong Yang; Chao Li 033; Wei Liu 005; Jian Luan 001; Zenglin Xu (CoRR, 2025)

Simple Yet Effective: Extracting Private Data Across Clients in Federated Fine-Tuning of Large Language Models. - Yingqi Hu; Zhuo Zhang 007; Jingyuan Zhang; Lizhen Qu; Zenglin Xu (CoRR, 2025)

Guideline Forest: Experience-Induced Multi-Guideline Reasoning with Stepwise Aggregation. - Jiaxiang Chen; Zhuo Wang; Mingxi Zou; Qifan Wang 001; Zenglin Xu (CoRR, 2025)

FinHEAR: Human Expertise and Adaptive Risk-Aware Temporal Reasoning for Financial Decision-Making. - Jiaxiang Chen; Mingxi Zou; Zhuo Wang; Qifan Wang 001; Dongning Sun; Chi Zhang; Zenglin Xu (CoRR, 2025)

Efficient Network Automatic Relevance Determination. - Hongwei Zhang; Ziqi Ye; Xinyuan Wang; Xin Guo 010; Zenglin Xu; Yuan Cheng; Zixin Hu; Yuan Qi 001 (CoRR, 2025)

SecFwT: Efficient Privacy-Preserving Fine-Tuning of Large Language Models Using Forward-Only Passes. - Jinglong Luo; Zhuo Zhang 007; Yehong Zhang; Shiyu Liu; Ye Dong; Xun Zhou 001; Hui Wang 013; Yue Yu 001; Zenglin Xu (CoRR, 2025)

Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification. - Langzhang Liang; Fanchen Bu; Zixing Song; Zenglin Xu; Shirui Pan; Kijung Shin (CoRR, 2025)

SlimRAG: Retrieval without Graphs via Entity-Aware Context Selection. - Jiale Zhang; Jiaxiang Chen; Zhucong Li; Jie Ding; Kui Zhao; Zenglin Xu; Xin Pang; Yinghui Xu (CoRR, 2025)

FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation. - Maolin Wang 001; Yutian Xiao; Binhao Wang; Sheng Zhang 028; Shanshan Ye; Wanyu Wang; Hongzhi Yin; Ruocheng Guo; Zenglin Xu (CoRR, 2025)

Advocating for the Silent: Enhancing Federated Generalization for Nonparticipating Clients. - Zheshun Wu; Zenglin Xu; Dun Zeng; Qifan Wang 001; Jie Liu 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)