Zenglin Xu

According to our database, Zenglin Xu authored at least 277 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Tackling Long-Tailed Distribution Issue in Graph Neural Networks via Normalization.

Langzhang Liang, Zenglin Xu, Zixing Song, Irwin King, Yuan Qi, Jieping Ye

IEEE Trans. Knowl. Data Eng., May, 2024

CGDD: Multiview Graph Clustering via Cross-Graph Diversity Detection.

Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

IEEE Trans. Neural Networks Learn. Syst., March, 2024

Adaptive asynchronous federated learning.

Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab

Future Gener. Comput. Syst., March, 2024

TopicAns: Topic-informed Architecture for Answer Recommendation on Technical Q&A Site.

Yuanhang Yang, Wei He, Cuiyun Gao, Zenglin Xu, Xin Xia, Chuanyi Liu

ACM Trans. Softw. Eng. Methodol., January, 2024

Information-Theoretic Generalization Analysis for Topology-Aware Heterogeneous Federated Edge Learning Over Noisy Channels.

Zheshun Wu, Zenglin Xu, Hongfang Yu, Jie Liu

IEEE Signal Process. Lett., 2024

MVEB: Self-Supervised Learning with Multi-View Entropy Bottleneck.

Liangjian Wen, Xiasi Wang, Jianzhuang Liu, Zenglin Xu

CoRR, 2024

Enhancing Efficiency in Sparse Models with Sparser Selection.

Yuanhang Yang, Shiyi Qi, Wenchao Gu, Chaozheng Wang, Cuiyun Gao, Zenglin Xu

CoRR, 2024

FedPIT: Towards Privacy-preserving and Few-shot Federated Instruction Tuning.

Zhuo Zhang, Jingyuan Zhang, Jintao Huang, Lizhen Qu, Hongzhi Zhang, Zenglin Xu

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

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, Yuan Qi

CoRR, 2024

Cumulative Distribution Function based General Temporal Point Processes.

Maolin Wang, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Zitao Liu, Langming Liu

CoRR, 2024

SecFormer: Towards Fast and Accurate Privacy-Preserving Inference for Large Language Models.

Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Xin Mu, Hui Wang, Yue Yu, Zenglin Xu

CoRR, 2024

A Survey on Scheduling Techniques in Computing and Network Convergence.

Shujiong Tang, Yue Yu, Hui Wang, Guiliang Wang, Wuhui Chen, Zenglin Xu, Song Guo, Wen Gao

IEEE Commun. Surv. Tutorials, 2024

OctOcc: High-Resolution 3D Occupancy Prediction with Octree.

Wenzhe Ouyang, Xiaolin Song, Bailan Feng, Zenglin Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks.

Junjie Chen, Jiahao Li, Chen Song, Bin Li, Qingcai Chen, Hongchang Gao, Wendy Hui Wang, Zenglin Xu, Xinghua Shi

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Preparing Lessons for Progressive Training on Language Models.

Yu Pan, Ye Yuan, Yichun Yin, Jiaxin Shi, Zenglin Xu, Ming Zhang, Lifeng Shang, Xin Jiang, Qun Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

RegNet: Self-Regulated Network for Image Classification.

Jing Xu, Yu Pan, Xinglin Pan, Steven C. H. Hoi, Zhang Yi, Zenglin Xu

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Graph-Based Semi-Supervised Learning: A Comprehensive Review.

Zixing Song, Xiangli Yang, Zenglin Xu, Irwin King

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Single image denoising with a feature-enhanced network.

Ruibin Zhuge, Jinghua Wang, Zenglin Xu, Yong Xu

Neural Networks, November, 2023

Boosting adversarial robustness via self-paced adversarial training.

Lirong He, Qingzhong Ai, Xincheng Yang, Yazhou Ren, Qifan Wang, Zenglin Xu

Neural Networks, October, 2023

A Survey on Deep Semi-Supervised Learning.

Xiangli Yang, Zixing Song, Irwin King, Zenglin Xu

IEEE Trans. Knowl. Data Eng., September, 2023

Multi-View Subspace Clustering by Joint Measuring of Consistency and Diversity.

Shudong Huang, Yixi Liu, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

IEEE Trans. Knowl. Data Eng., August, 2023

Latent Representation Guided Multi-View Clustering.

Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

IEEE Trans. Knowl. Data Eng., July, 2023

Stein Variational Gradient Descent with Multiple Kernels.

Qingzhong Ai, Shiyu Liu, Lirong He, Zenglin Xu

Cogn. Comput., March, 2023

Learning to generate complex question with intent prediction from long passage.

Youcheng Pan, Baotian Hu, Shiyue Wang, Xiaolong Wang, Qingcai Chen, Zenglin Xu, Min Zhang

Appl. Intell., March, 2023

FedLab: A Flexible Federated Learning Framework.

Dun Zeng, Siqi Liang, Xiangjing Hu, Hui Wang, Zenglin Xu

J. Mach. Learn. Res., 2023

Edge enhancement improves adversarial robustness in image classification.

Lirong He, Qingzhong Ai, Yuqing Lei, Lili Pan, Yazhou Ren, Zenglin Xu

Neurocomputing, 2023

Topology Learning for Heterogeneous Decentralized Federated Learning over Unreliable D2D Networks.

Zheshun Wu, Zenglin Xu, Dun Zeng, Junfan Li, Jie Liu

CoRR, 2023

On Diversified Preferences of Large Language Model Alignment.

Dun Zeng, Yong Dai, Pengyu Cheng, Tianhao Hu, Wanshun Chen, Nan Du, Zenglin Xu

CoRR, 2023

Information-Theoretic Generalization Analysis for Topology-aware Heterogeneous Federated Edge Learning over Noisy Channels.

Zheshun Wu, Zenglin Xu, Hongfang Yu, Jie Liu

CoRR, 2023

Reusing Pretrained Models by Multi-linear Operators for Efficient Training.

Yu Pan, Ye Yuan, Yichun Yin, Zenglin Xu, Lifeng Shang, Xin Jiang, Qun Liu

CoRR, 2023

Federated Generalization via Information-Theoretic Distribution Diversification.

Zheshun Wu, Zenglin Xu, Dun Zeng, Qifan Wang

CoRR, 2023

Less is More: On the Feature Redundancy of Pretrained Models When Transferring to Few-shot Tasks.

Xu Luo, Difan Zou, Lianli Gao, Zenglin Xu, Jingkuan Song

CoRR, 2023

Tackling Hybrid Heterogeneity on Federated Optimization via Gradient Diversity Maximization.

Dun Zeng, Zenglin Xu, Yu Pan, Qifan Wang, Xiaoying Tang

CoRR, 2023

Exploring Federated Optimization by Reducing Variance of Adaptive Unbiased Client Sampling.

Dun Zeng, Zenglin Xu, Yu Pan, Qifan Wang, Xiaoying Tang

CoRR, 2023

Personalized Federated Learning via Amortized Bayesian Meta-Learning.

Shiyu Liu, Shaogao Lv, Dun Zeng, Zenglin Xu, Hui Wang, Yue Yu

CoRR, 2023

FedNoisy: Federated Noisy Label Learning Benchmark.

Siqi Liang, Jintao Huang, Dun Zeng, Junyuan Hong, Jiayu Zhou, Zenglin Xu

CoRR, 2023

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

CoRR, 2023

Tensorized Hypergraph Neural Networks.

Maolin Wang, Yaoming Zhen, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao

CoRR, 2023

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping.

Zhe Li, Shiyi Qi, Yiduo Li, Zenglin Xu

CoRR, 2023

BadCS: A Backdoor Attack Framework for Code search.

Shiyi Qi, Yuanhang Yang, Shuzheng Gao, Cuiyun Gao, Zenglin Xu

CoRR, 2023

Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition.

Ying Mo, Hongyin Tang, Jiahao Liu, Qifan Wang, Zenglin Xu, Jingang Wang, Wei Wu, Zhoujun Li

CoRR, 2023

Stochastic Clustered Federated Learning.

Dun Zeng, Xiangjing Hu, Shiyu Liu, Yue Yu, Qifan Wang, Zenglin Xu

CoRR, 2023

Tensor Networks Meet Neural Networks: A Survey.

Maolin Wang, Yu Pan, Xiangli Yang, Guangxi Li, 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

Ti-MAE: Self-Supervised Masked Time Series Autoencoders.

Zhe Li, Zhongwen Rao, Lujia Pan, Pengyun Wang, Zenglin Xu

CoRR, 2023

A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy.

Yifei Zhang, Dun Zeng, Jinglong Luo, Zenglin Xu, Irwin King

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

1st Workshop on Federated Learning Technologies.

Mirko Polato, Roberto Esposito, Walter Riviera, Zenglin Xu, Irwin King

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Practical privacy-preserving Gaussian process regression via secret sharing.

Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Shuang Qin, Hui Wang, Yue Yu, Zenglin Xu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily.

Langzhang Liang, Xiangjing Hu, Zenglin Xu, Zixing Song, Irwin King

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reusing Pretrained Models by Multi-linear Operators for Efficient Training.

Yu Pan, Ye Yuan, Yichun Yin, Zenglin Xu, Lifeng Shang, Xin Jiang, Qun Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Flexible Contribution Estimation Methods for Horizontal Federated Learning.

Xiangjing Hu, Congjian Luo, Dun Zeng, Zenglin Xu, Ping Guo, Irwin King

Proceedings of the International Joint Conference on Neural Networks, 2023

Prompt Learns Prompt: Exploring Knowledge-Aware Generative Prompt Collaboration For Video Captioning.

Liqi Yan, Cheng Han, Zenglin Xu, Dongfang Liu, Qifan Wang

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 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

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Contrastive Kernel Subspace Clustering.

Qian Zhang, Zhao Kang, Zenglin Xu, Hongguang Fu

Proceedings of the Neural Information Processing - 30th International Conference, 2023

Generalized Category Discovery with Clustering Assignment Consistency.

Xiangli Yang, Xinglin Pan, Irwin King, Zenglin Xu

Proceedings of the Neural Information Processing - 30th International Conference, 2023

Quantized SGD in Federated Learning: Communication, Optimization and Generalization.

Shiyu Liu, Linsen Wei, Shaogao Lv, Zenglin Xu

Proceedings of the Neural Information Processing - 30th International Conference, 2023

Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization.

Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao

Proceedings of the IEEE International Conference on Data Mining, 2023

MHCN: A Hyperbolic Neural Network Model for Multi-view Hierarchical Clustering.

Fangfei Lin, Bing Bai, Yiwen Guo, Hao Chen, Yazhou Ren, Zenglin Xu

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Multi-Task Transformer with Relation-Attention and Type-Attention for Named Entity Recognition.

Ying Mo, Hongyin Tang, Jiahao Liu, Qifan Wang, Zenglin Xu, Jingang Wang, Wei Wu, Zhoujun Li

Proceedings of the IEEE International Conference on Acoustics, 2023

Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling.

Yuanhang Yang, Shiyi Qi, Chuanyi Liu, Qifan Wang, Cuiyun Gao, Zenglin Xu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

APrompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models.

Qifan Wang, Yuning Mao, Jingang Wang, Hanchao Yu, Shaoliang Nie, Sinong Wang, Fuli Feng, Lifu Huang, Xiaojun Quan, Zenglin Xu, Dongfang Liu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 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, Zenglin Xu

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Generative Oversampling for Imbalanced Data via Majority-Guided VAE.

Qingzhong Ai, Pengyun Wang, Lirong He, Liangjian Wen, Lujia Pan, Zenglin Xu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models.

Zhuo Zhang, Yuanhang Yang, Yong Dai, Qifan Wang, Yue Yu, Lizhen Qu, Zenglin Xu

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP.

Zhuo Zhang, Xiangjing Hu, Jingyuan Zhang, Yating Zhang, Hui Wang, Lizhen Qu, Zenglin Xu

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

MixPAVE: Mix-Prompt Tuning for Few-shot Product Attribute Value Extraction.

Li Yang, Qifan Wang, Jingang Wang, Xiaojun Quan, Fuli Feng, Yu Chen, Madian Khabsa, Sinong Wang, Zenglin Xu, Dongfang Liu

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

MUSTIE: Multimodal Structural Transformer for Web Information Extraction.

Qifan Wang, Jingang Wang, Xiaojun Quan, Fuli Feng, Zenglin Xu, Shaoliang Nie, Sinong Wang, Madian Khabsa, Hamed Firooz, Dongfang Liu

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering.

Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

ESync: Accelerating Intra-Domain Federated Learning in Heterogeneous Data Centers.

Zonghang Li, Huaman Zhou, Tianyao Zhou, Hongfang Yu, Zenglin Xu, Gang Sun

IEEE Trans. Serv. Comput., 2022

Improved Inference for Imputation-Based Semisupervised Learning Under Misspecified Setting.

Shaogao Lv, Linsen Wei, Qian Zhang, Bin Liu, Zenglin Xu

IEEE Trans. Neural Networks Learn. Syst., 2022

Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-View Clustering.

Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

IEEE Trans. Knowl. Data Eng., 2022

Efficient federated multi-view learning.

Shudong Huang, Wei Shi, Zenglin Xu, Ivor W. Tsang, Jiancheng Lv

Pattern Recognit., 2022

AFINet: Attentive Feature Integration Networks for image classification.

Xinglin Pan, Jing Xu, Yu Pan, Liangjian Wen, Wenxiang Lin, Kun Bai, Hongguang Fu, Zenglin Xu

Neural Networks, 2022

Re-thinking model robustness from stability: a new insight to defend adversarial examples.

Shufei Zhang, Kaizhu Huang, Zenglin Xu

Mach. Learn., 2022

Multiple partitions alignment via spectral rotation.

Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

Mach. Learn., 2022

Spaks: Self-paced multiple kernel subspace clustering with feature smoothing regularization.

Qian Zhang, Zhao Kang, Zenglin Xu, Shudong Huang, Hongguang Fu

Knowl. Based Syst., 2022

Graph Fusion Network for Text Classification.

Yong Dai, Linjun Shou, Ming Gong, Xiaolin Xia, Zhao Kang, Zenglin Xu, Daxin Jiang

Knowl. Based Syst., 2022

Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT.

Zonghang Li, Yihong He, Hongfang Yu, Jiawen Kang, Xiaoping Li, Zenglin Xu, Dusit Niyato

IEEE Internet Things J., 2022

Non-uniform Nyström approximation for sparse kernel regression: Theoretical analysis and experimental evaluation.

Qian Zhang, Wei Shi, Steven Hoi, Zenglin Xu

Neurocomputing, 2022

TedNet: A Pytorch toolkit for tensor decomposition networks.

Yu Pan, Maolin Wang, Zenglin Xu

Neurocomputing, 2022

When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods.

Zhuo Zhang, Yuanhang Yang, Yong Dai, Lizhen Qu, Zenglin Xu

CoRR, 2022

MultiCoder: Multi-Programming-Lingual Pre-Training for Low-Resource Code Completion.

Zi Gong, Yinpeng Guo, Pingyi Zhou, Cuiyun Gao, Yasheng Wang, Zenglin Xu

CoRR, 2022

Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling.

Yuanhang Yang, Shiyi Qi, Cuiyun Gao, Zenglin Xu, Yulan He, Qifan Wang, Chuanyi Liu

CoRR, 2022

A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities.

Yaoxian Li, Shiyi Qi, Cuiyun Gao, Yun Peng, David Lo, Zenglin Xu, Michael R. Lyu

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

Aggregating Gradients in Encoded Domain for Federated Learning.

Dun Zeng, Shiyu Liu, Zenglin Xu

CoRR, 2022

MarkBERT: Marking Word Boundaries Improves Chinese BERT.

Linyang Li, Yong Dai, Duyu Tang, Zhangyin Feng, Cong Zhou, Xipeng Qiu, Zenglin Xu, Shuming Shi

CoRR, 2022

Source Code Summarization with Structural Relative Position Guided Transformer.

Zi Gong, Cuiyun Gao, Yasheng Wang, Wenchao Gu, Yun Peng, Zenglin Xu

Proceedings of the IEEE International Conference on Software Analysis, 2022

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid.

Jing Xu, Xu Luo, Xinglin Pan, Yanan Li, Wenjie Pei, Zenglin Xu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-view Subspace Clustering on Topological Manifold.

Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Smooth Representation for Multi-view Subspace Clustering.

Shudong Huang, Yixi Liu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

ACE: A Coarse-to-Fine Learning Framework for Reliable Representation Learning Against Label Noise.

Chenbin Zhang, Xiangli Yang, Jian Liang, Bing Bai, Kun Bai, Irwin King, Zenglin Xu

Proceedings of the International Joint Conference on Neural Networks, 2022

Contrastive Multi-view Hyperbolic Hierarchical Clustering.

Fangfei Lin, Bing Bai, Kun Bai, Yazhou Ren, Peng Zhao, Zenglin Xu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Channel Importance Matters in Few-Shot Image Classification.

Xu Luo, Jing Xu, Zenglin Xu

Proceedings of the International Conference on Machine Learning, 2022

A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks.

Yu Pan, Zeyong Su, Ao Liu, Jingquan Wang, Nannan Li, Zenglin Xu

Proceedings of the International Conference on Machine Learning, 2022

Field-aware Variational Autoencoders for Billion-scale User Representation Learning.

Ge Fan, Chaoyun Zhang, Junyang Chen, Baopu Li, Zenglin Xu, Yingjie Li, Luyu Peng, Zhiguo Gong

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Semantically Proportional Patchmix for Few-Shot Learning.

Jingquan Wang, Jing Xu, Yu Pan, Zenglin Xu

Proceedings of the IEEE International Conference on Acoustics, 2022

Federated Model Decomposition with Private Vocabulary for Text Classification.

Zhuo Zhang, Xiangjing Hu, Lizhen Qu, Qifan Wang, Zenglin Xu

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

SMARTAVE: Structured Multimodal Transformer for Product Attribute Value Extraction.

Qifan Wang, Li Yang, Jingang Wang, Jitin Krishnan, Bo Dai, Sinong Wang, Zenglin Xu, Madian Khabsa, Hao Ma

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Learning to Generate Question by Asking Question: A Primal-Dual Approach with Uncommon Word Generation.

Qifan Wang, Li Yang, Xiaojun Quan, Fuli Feng, Dongfang Liu, Zenglin Xu, Sinong Wang, Hao Ma

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Leveraging Only the Category Name for Aspect Detection through Prompt-based Constrained Clustering.

Yazheng Li, Pengyun Wang, Yasheng Wang, Yong Dai, Yadao Wang, Lujia Pan, Zenglin Xu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training.

Shenglai Zeng, Zonghang Li, Hongfang Yu, Yihong He, Zenglin Xu, Dusit Niyato, Han Yu

Proceedings of the Database Systems for Advanced Applications, 2022

Multi-View Clustering on Topological Manifold.

Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Pseudo-Supervised Deep Subspace Clustering.

Juncheng Lv, Zhao Kang, Xiao Lu, Zenglin Xu

IEEE Trans. Image Process., 2021

Structured graph learning for clustering and semi-supervised classification.

Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian

Pattern Recognit., 2021

Robust deep k-means: An effective and simple method for data clustering.

Shudong Huang, Zhao Kang, Zenglin Xu, Quanhui Liu

Pattern Recognit., 2021

CRaDLe: Deep code retrieval based on semantic Dependency Learning.

Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, Hongyu Zhang, Zenglin Xu, Michael R. Lyu

Neural Networks, 2021

Byzantine Resistant Secure Blockchained Federated Learning at the Edge.

Zonghang Li, Hongfang Yu, Tianyao Zhou, Long Luo, Mochan Fan, Zenglin Xu, Gang Sun

IEEE Netw., 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

Deep embedded multi-view clustering with collaborative training.

Jie Xu, Yazhou Ren, Guofeng Li, Lili Pan, Ce Zhu, Zenglin Xu

Inf. Sci., 2021

Multi-view subspace clustering via partition fusion.

Juncheng Lv, Zhao Kang, Boyu Wang, Luping Ji, Zenglin Xu

Inf. Sci., 2021

Domain adaptation with feature and label adversarial networks.

Peng Zhao, Wenhua Zang, Bin Liu, Zhao Kang, Kun Bai, Kaizhu Huang, Zenglin Xu

Neurocomputing, 2021

MultiFace: A generic training mechanism for boosting face recognition performance.

Jing Xu, Tszhang Guo, Yong Xu, Zenglin Xu, Kun Bai

Neurocomputing, 2021

CoreGen: Contextualized Code Representation Learning for Commit Message Generation.

Lun Yiu Nie, Cuiyun Gao, Zhicong Zhong, Wai Lam, Yang Liu, Zenglin Xu

Neurocomputing, 2021

Machine learning based early mortality prediction in the emergency department.

Cong Li, Zhuo Zhang, Yazhou Ren, Hu Nie, Yuqing Lei, Hang Qiu, Zenglin Xu, Xiaorong Pu

Int. J. Medical Informatics, 2021

Exploring Category-correlated Feature for Few-shot Image Classification.

Jing Xu, Xinglin Pan, Xu Luo, Wenjie Pei, Zenglin Xu

CoRR, 2021

Self-Paced Deep Regression Forests with Consideration on Ranking Fairness.

Lili Pan, Mingming Meng, Yazhou Ren, Yali Zheng, Zenglin Xu

CoRR, 2021

Label-Aware Distribution Calibration for Long-tailed Classification.

Chaozheng Wang, Shuzheng Gao, Cuiyun Gao, Pengyun Wang, Wenjie Pei, Lujia Pan, Zenglin Xu

CoRR, 2021

Graph Partner Neural Networks for Semi-Supervised Learning on Graphs.

Langzhang Liang, Cuiyun Gao, Shiyi Chen, Shishi Duan, Yu Pan, Junjin Zheng, Lei Wang, Zenglin Xu

CoRR, 2021

FedLab: A Flexible Federated Learning Framework.

Dun Zeng, Siqi Liang, Xiangjing Hu, Zenglin Xu

CoRR, 2021

Kernel Selection for Stein Variational Gradient Descent.

Qingzhong Ai, Shiyu Liu, Zenglin Xu

CoRR, 2021

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE.

Qingzhong Ai, Lirong He, Liangjian Wen, Shiyu Liu, Zenglin Xu

CoRR, 2021

Rectifying the Shortcut Learning of Background: Shared Object Concentration for Few-Shot Image Recognition.

Xu Luo, Longhui Wei, Liangjian Wen, Jinrong Yang, Lingxi Xie, Zenglin Xu, Qi Tian

CoRR, 2021

AFINet: Attentive Feature Integration Networks for Image Classification.

Xinglin Pan, Jing Xu, Yu Pan, Liangjian Wen, Wenxiang Lin, Kun Bai, Zenglin Xu

CoRR, 2021

Partial Differential Equations is All You Need for Generating Neural Architectures - A Theory for Physical Artificial Intelligence Systems.

Ping Guo, Kaizhu Huang, Zenglin Xu

CoRR, 2021

Contrastive Disentanglement in Generative Adversarial Networks.

Lili Pan, Peijun Tang, Zhiyong Chen, Zenglin Xu

CoRR, 2021

MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance.

Jing Xu, Tszhang Guo, Zenglin Xu, Kun Bai

CoRR, 2021

Unsupervised Sentiment Analysis by Transferring Multi-source Knowledge.

Yong Dai, Jian Liu, Jian Zhang, Hongguang Fu, Zenglin Xu

Cogn. Comput., 2021

Creating and Evaluating Resources for Sentiment Analysis in the Low-resource Language: Sindhi.

Wazir Ali, Naveed Ali, Yong Dai, Jay Kumar, Saifullah Tumrani, Zenglin Xu

Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, 2021

Rectifying the Shortcut Learning of Background for Few-Shot Learning.

Xu Luo, Longhui Wei, Liangjian Wen, Jinrong Yang, Lingxi Xie, Zenglin Xu, Qi Tian

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE.

Qingzhong Ai, Lirong He, Shiyu Liu, Zenglin Xu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CDD: Multi-view Subspace Clustering via Cross-view Diversity Detection.

Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Angular Triplet Loss-based Camera Network for ReID.

Yitian Li, Ruini Xue, Mengmeng Zhu, Jing Xu, Zenglin Xu

Proceedings of the International Joint Conference on Neural Networks, 2021

Discrete Auto-regressive Variational Attention Models for Text Modeling.

Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael R. Lyu, Irwin King

Proceedings of the International Joint Conference on Neural Networks, 2021

Boosting Few-Shot Classification with View-Learnable Contrastive Learning.

Xu Luo, Yuxuan Chen, Liangjian Wen, Lili Pan, Zenglin Xu

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Robustness of Combined sEMG and Ultrasound Modalities Against Muscle Fatigue in Force Estimation.

Jia Zeng, Yu Zhou, Yicheng Yang, Zenglin Xu, Hongwei Zhang, Honghai Liu

Proceedings of the Intelligent Robotics and Applications - 14th International Conference, 2021

2020

Multi-document semantic relation extraction for news analytics.

Yongpan Sheng, Zenglin Xu, Yafang Wang, Gerard de Melo

World Wide Web, 2020

Robust Graph Learning From Noisy Data.

Zhao Kang, Haiqi Pan, Steven C. H. Hoi, Zenglin Xu

IEEE Trans. Cybern., 2020

Auto-weighted multi-view clustering via deep matrix decomposition.

Shudong Huang, Zhao Kang, Zenglin Xu

Pattern Recognit., 2020

Block-term tensor neural networks.

Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang, Shandian Zhe, 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

Latent Dirichlet allocation based generative adversarial networks.

Lili Pan, Shen Cheng, Jian Liu, Peijun Tang, Bowen Wang, Yazhou Ren, Zenglin Xu

Neural Networks, 2020

Partition level multiview subspace clustering.

Zhao Kang, Xinjia Zhao, Chong Peng, Hongyuan Zhu, Joey Tianyi Zhou, Xi Peng, Wenyu Chen, Zenglin Xu

Neural Networks, 2020

Structure learning with similarity preserving.

Zhao Kang, Xiao Lu, Yiwei Lu, Chong Peng, Wenyu Chen, Zenglin Xu

Neural Networks, 2020

Relation-Guided Representation Learning.

Zhao Kang, Xiao Lu, Jian Liang, Kun Bai, Zenglin Xu

Neural Networks, 2020

DART: Domain-Adversarial Residual-Transfer networks for unsupervised cross-domain image classification.

Xianghong Fang, Haoli Bai, Ziyi Guo, Bin Shen, Steven C. H. Hoi, Zenglin Xu

Neural Networks, 2020

Deep density-based image clustering.

Yazhou Ren, Ni Wang, Mingxia Li, Zenglin Xu

Knowl. Based Syst., 2020

Multi-graph fusion for multi-view spectral clustering.

Zhao Kang, Guoxin Shi, Shudong Huang, Wenyu Chen, Xiaorong Pu, Joey Tianyi Zhou, Zenglin Xu

Knowl. Based Syst., 2020

Auto-weighted multi-view co-clustering with bipartite graphs.

Shudong Huang, Zenglin Xu, Ivor W. Tsang, Zhao Kang

Inf. Sci., 2020

Self-paced and auto-weighted multi-view clustering.

Yazhou Ren, Shudong Huang, Peng Zhao, Minghao Han, Zenglin Xu

Neurocomputing, 2020

Two birds with one stone: Transforming and generating facial images with iterative GAN.

Dan Ma, Bin Liu, Zhao Kang, Jiayu Zhou, Jianke Zhu, Zenglin Xu

Neurocomputing, 2020

Regularized nonnegative matrix factorization with adaptive local structure learning.

Shudong Huang, Zenglin Xu, Zhao Kang, Yazhou Ren

Neurocomputing, 2020

A Subword Guided Neural Word Segmentation Model for Sindhi.

Wazir Ali, Jay Kumar, Zenglin Xu, Congjian Luo, Junyu Lu, Junming Shao, Rajesh Kumar, Yazhou Ren

CoRR, 2020

Heuristic Rank Selection with Progressively Searching Tensor Ring Network.

Nannan Li, Yu Pan, Yaran Chen, Zixiang Ding, Dongbin Zhao, Zenglin Xu

CoRR, 2020

Structured Graph Learning for Clustering and Semi-supervised Classification.

Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian

CoRR, 2020

Contextualized Code Representation Learning for Commit Message Generation.

Lun Yiu Nie, Cuiyun Gao, Zhicong Zhong, Wai Lam, Yang Liu, Zenglin Xu

CoRR, 2020

ReadNet: Towards Accurate ReID with Limited and Noisy Samples.

Yitian Li, Ruini Xue, Mengmeng Zhu, Qing Xu, Zenglin Xu

CoRR, 2020

Discrete Variational Attention Models for Language Generation.

Xianghong Fang, Haoli Bai, Zenglin Xu, Michael R. Lyu, Irwin King

CoRR, 2020

Self-Paced Deep Regression Forests with Consideration on Underrepresented Samples.

Lili Pan, Shijie Ai, Yazhou Ren, Zenglin Xu

CoRR, 2020

A combination model based on transfer learning for waste classification.

Guang-Li Huang, Jing He, Zenglin Xu, Guangyan Huang

Concurr. Comput. Pract. Exp., 2020

Knowledge Fusion via Joint Tensor and Matrix Factorization.

Zengguang Hao, Yafang Wang, Zining Liu, Gerard de Melo, Zenglin Xu

Cogn. Comput., 2020

Combining Multi-Perspective Attention Mechanism With Convolutional Networks for Monaural Speech Enhancement.

Tian Lan, Yilan Lyu, Wenzheng Ye, Guoqiang Hui, Zenglin Xu, Qiao Liu

IEEE Access, 2020

Read, Attend, and Exclude: Multi-Choice Reading Comprehension by Mimicking Human Reasoning Process.

Chenbin Zhang, Congjian Luo, Junyu Lu, Ao Liu, Bing Bai, Kun Bai, Zenglin Xu

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Improving Contextual Language Models for Response Retrieval in Multi-Turn Conversation.

Junyu Lu, Xiancong Ren, Yazhou Ren, Ao Liu, Zenglin Xu

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Multi-Level Multimodal Transformer Network for Multimodal Recipe Comprehension.

Ao Liu, Shuai Yuan, Chenbin Zhang, Congjian Luo, Yaqing Liao, Kun Bai, Zenglin Xu

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Deep K-Means: A Simple and Effective Method for Data Clustering.

Shudong Huang, Zhao Kang, Zenglin Xu

Proceedings of the Neural Computing for Advanced Applications, 2020

SiNER: A Large Dataset for Sindhi Named Entity Recognition.

Wazir Ali, Junyu Lu, Zenglin Xu

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Learning to Search Efficient DenseNet with Layer-wise Pruning.

Xuanyang Zhang, Hao Liu, Zhanxing Zhu, Zenglin Xu

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Concatenated Tensor Networks for Deep Multi-Task Learning.

Maolin Wang, Zeyong Su, Xu Luo, Yu Pan, Shenggen Zheng, Zenglin Xu

Proceedings of the Neural Information Processing - 27th International Conference, 2020

Causal Inference for Mixed-Type Data in Additive Noise Models.

Xin Liu, Zenglin Xu, Ping Guo

Proceedings of the Neural Information Processing - 27th International Conference, 2020

Mutual Information Gradient Estimation for Representation Learning.

Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu

Proceedings of the 8th International Conference on Learning Representations, 2020

Self-Paced Deep Regression Forests with Consideration on Underrepresented Examples.

Lili Pan, Shijie Ai, Yazhou Ren, Zenglin Xu

Proceedings of the Computer Vision - ECCV 2020, 2020

Large-Scale Multi-View Subspace Clustering in Linear Time.

Zhao Kang, Wangtao Zhou, Zhitong Zhao, Junming Shao, Meng Han, Zenglin Xu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis.

Yong Dai, Jian Liu, Xiancong Ren, Zenglin Xu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Variational Random Function Model for Network Modeling.

Zenglin Xu, Bin Liu, Shandian Zhe, Haoli Bai, Zihan Wang, Jennifer Neville

IEEE Trans. Neural Networks Learn. Syst., 2019

Auto-weighted multi-view clustering via kernelized graph learning.

Shudong Huang, Zhao Kang, Ivor W. Tsang, Zenglin Xu

Pattern Recognit., 2019

Low-rank kernel learning for graph-based clustering.

Zhao Kang, Liangjian Wen, Wenyu Chen, Zenglin Xu

Knowl. Based Syst., 2019

Self-paced and soft-weighted nonnegative matrix factorization for data representation.

Shudong Huang, Peng Zhao, Yazhou Ren, Tianrui Li, Zenglin Xu

Knowl. Based Syst., 2019

Self-paced multi-task clustering.

Yazhou Ren, Xiaofan Que, Dezhong Yao, Zenglin Xu

Neurocomputing, 2019

Parallel boosted clustering.

Yazhou Ren, Uday Kamath, Carlotta Domeniconi, Zenglin Xu

Neurocomputing, 2019

Semi-supervised deep embedded clustering.

Yazhou Ren, Kangrong Hu, Xinyi Dai, Lili Pan, Steven C. H. Hoi, Zenglin Xu

Neurocomputing, 2019

Clustering with similarity preserving.

Zhao Kang, Honghui Xu, Boyu Wang, Hongyuan Zhu, Zenglin Xu

Neurocomputing, 2019

Structure Learning with Similarity Preserving.

Zhao Kang, Xiao Lu, Yiwei Lu, Chong Peng, 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

Structured Pruning of Recurrent Neural Networks through Neuron Selection.

Liangjiang Wen, Xueyang Zhang, Haoli Bai, Zenglin Xu

CoRR, 2019

Tensor Ring Restricted Boltzmann Machines.

Maolin Wang, Chenbin Zhang, Yu Pan, Jing Xu, Zenglin Xu

Proceedings of the International Joint Conference on Neural Networks, 2019

Multiple Partitions Aligned Clustering.

Zhao Kang, Zipeng Guo, Shudong Huang, Siying Wang, Wenyu Chen, Yuanzhang Su, Zenglin Xu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Adversarial Noise Layer: Regularize Neural Network by Adding Noise.

Zhonghui You, Jinmian Ye, Kunming Li, Zenglin Xu, Ping Wang

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Deep Minimax Probability Machine.

Lirong He, Ziyi Guo, Kaizhu Huang, Zenglin Xu

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

A Two-Stage Multi-task Learning-Based Method for Selective Unsupervised Domain Adaptation.

Yong Dai, Jian Zhang, Shuai Yuan, Zenglin Xu

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Additive Adversarial Learning for Unbiased Authentication.

Jian Liang, Yuren Cao, Chenbin Zhang, Shiyu Chang, Kun Bai, Zenglin Xu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Machine Reading Comprehension: Matching and Orders.

Ao Liu, Lizhen Qu, Junyu Lu, Chenbin Zhang, Zenglin Xu

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Coherence and Salience-Based Multi-Document Relationship Mining.

Yongpan Sheng, Zenglin Xu

Proceedings of the Web and Big Data - Third International Joint Conference, 2019

Constructing Interpretive Spatio-Temporal Features for Multi-Turn Responses Selection.

Junyu Lu, Chenbin Zhang, Zeying Xie, Guang Ling, Tom Chao Zhou, Zenglin Xu

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition.

Yu Pan, Jing Xu, Maolin Wang, Jinmian Ye, Fei Wang, Kun Bai, Zenglin Xu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Similarity Learning via Kernel Preserving Embedding.

Zhao Kang, Yiwei Lu, Yuanzhang Su, Changsheng Li, Zenglin Xu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Manifold regularized matrix completion for multi-label learning with ADMM.

Bin Liu, Yingming Li, Zenglin Xu

Neural Networks, 2018

Adaptive local structure learning for document co-clustering.

Shudong Huang, Zenglin Xu, Jiancheng Lv

Knowl. Based Syst., 2018

Self-weighted multi-view clustering with soft capped norm.

Shudong Huang, Zhao Kang, Zenglin Xu

Knowl. Based Syst., 2018

Robust multi-view data clustering with multi-view capped-norm K-means.

Shudong Huang, Yazhou Ren, Zenglin Xu

Neurocomputing, 2018

TensorD: A tensor decomposition library in TensorFlow.

Liyang Hao, Siqi Liang, Jinmian Ye, Zenglin Xu

Neurocomputing, 2018

Robust graph regularized nonnegative matrix factorization for clustering.

Shudong Huang, Hongjun Wang, Tao Li, Tianrui Li, Zenglin Xu

Data Min. Knowl. Discov., 2018

Latent Dirichlet Allocation in Generative Adversarial Networks.

Lili Pan, Shen Cheng, Jian Liu, Yazhou Ren, Zenglin Xu

CoRR, 2018

NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition.

Bin Liu, Lirong He, Yingming Li, Shandian Zhe, Zenglin Xu

Cogn. Comput., 2018

Knowledge Base Completion by Variational Bayesian Neural Tensor Decomposition.

Lirong He, Bin Liu, Guangxi Li, Yongpan Sheng, Yafang Wang, Zenglin Xu

Cogn. Comput., 2018

Semi-supervised DenPeak Clustering with Pairwise Constraints.

Yazhou Ren, Xiaohui Hu, Ke Shi, Guoxian Yu, Dezhong Yao, Zenglin Xu

Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Superneurons: dynamic GPU memory management for training deep neural networks.

Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 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

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 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

Proceedings of the ISICDM 2018: The 2nd International Symposium on Image Computing and Digital Medicine 2018, 2018

Structured Inference for Recurrent Hidden Semi-markov Model.

Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification.

Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Association Study of Alzheimer's Disease with Tree-Guided Sparse Canonical Correlation Analysis.

Shangchen Zhou, Shuai Yuan, Zhizhuo Zhang, Zenglin Xu

Proceedings of the Neural Information Processing - 25th International Conference, 2018

Self-Paced Multi-Task Multi-View Capped-norm Clustering.

Yazhou Ren, Xin Yan, Zechuan Hu, Zenglin Xu

Proceedings of the Neural Information Processing - 25th International Conference, 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

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Neural Relational Topic Models for Scientific Article Analysis.

Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Learning With Incomplete Labels.

Yingming Li, Zenglin Xu, Zhongfei Zhang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Unified Spectral Clustering With Optimal Graph.

Zhao Kang, Chong Peng, Qiang Cheng, Zenglin Xu

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

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

Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs.

Dan Ma, Bin Liu, Zhao Kang, Jianke Zhu, Zenglin Xu

CoRR, 2017

Stochastic Sequential Neural Networks with Structured Inference.

Hao Liu, Haoli Bai, Lirong He, Zenglin Xu

CoRR, 2017

Efficient Communications in Training Large Scale Neural Networks.

Yiyang Zhao, Linnan Wang, Wei Wu, George Bosilca, Richard W. Vuduc, Jinmian Ye, Wenqi Tang, Zenglin Xu

Proceedings of the on Thematic Workshops of ACM Multimedia 2017, Mountain View, CA, USA, October 23, 2017

Link prediction by exploiting network formation games in exchangeable graphs.

Liqiang Wang, Yafang Wang, Bin Liu, Lirong He, Shijun Liu, Gerard de Melo, Zenglin Xu

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Balanced self-paced learning with feature corruption.

Yazhou Ren, Peng Zhao, Zenglin Xu, Dezhong Yao

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Learning from semantically dependent multi-tasks.

Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, Shandian Zhe

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Simple and efficient parallelization for probabilistic temporal tensor factorization.

Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King, Michael R. Lyu

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Nonnegative matrix factorization with adaptive neighbors.

Shudong Huang, Zenglin Xu, Fei Wang

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Robust Softmax Regression for Multi-class Classification with Self-Paced Learning.

Yazhou Ren, Peng Zhao, Yongpan Sheng, Dezhong Yao, Zenglin Xu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Regularized Multi-source Matrix Factorization for Diagnosis of Alzheimer's Disease.

Xiaofan Que, Yazhou Ren, Jiayu Zhou, Zenglin Xu

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Learning with Feature Network and Label Network Simultaneously.

Yingming Li, Ming Yang, Zenglin Xu, Zhongfei (Mark) Zhang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Manifold regularized matrix completion for multilabel classification.

Bin Liu, Zenglin Xu, Shuang Wu, Fei Wang

Pattern Recognit. Lett., 2016

Association Discovery and Diagnosis of Alzheimer's Disease with Bayesian Multiview Learning.

Zenglin Xu, Shandian Zhe, Yuan Qi, Peng Yu

J. Artif. Intell. Res., 2016

Distributed Flexible Nonlinear Tensor Factorization.

Shandian Zhe, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu, Jian Yang, Youngja Park, Yuan Qi

CoRR, 2016

Distributed Flexible Nonlinear Tensor Factorization.

Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Consensus Guided Multiple Match Removal for Geometry Verification in Image Retrieval.

Hong Wu, Xing Heng, Zenglin Xu

Proceedings of the MultiMedia Modeling - 22nd International Conference, 2016

Multi-View Learning with Limited and Noisy Tagging.

Yingming Li, Ming Yang, Zenglin Xu, Zhongfei (Mark) Zhang

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing.

Linnan Wang, Wei Wu, Zenglin Xu, Jianxiong Xiao, Yi Yang

Proceedings of the 2016 International Conference on Supercomputing, 2016

Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network.

Haoli Bai, Zenglin Xu, Bin Liu, Yingming Li

Proceedings of The 8th Asian Conference on Machine Learning, 2016

DinTucker: Scaling Up Gaussian Process Models on Large Multidimensional Arrays.

Shandian Zhe, Yuan Qi, Youngja Park, Zenglin Xu, Ian M. Molloy, Suresh Chari

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Learning with Marginalized Corrupted Features and Labels Together.

Yingming Li, Ming Yang, Zenglin Xu, Zhongfei (Mark) Zhang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Bayesian Nonparametric Models for Multiway Data Analysis.

Zenglin Xu, Feng Yan, Yuan (Alan) Qi

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Budget constrained non-monotonic feature selection.

Haiqin Yang, Zenglin Xu, Michael R. Lyu, Irwin King

Neural Networks, 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

Proceedings of the Computer Security - ESORICS 2015, 2015

Scalable Nonparametric Multiway Data Analysis.

Shandian Zhe, Zenglin Xu, Xinqi Chu, Yuan (Alan) Qi, Youngja Park

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Sparse Bayesian Multiview Learning for Simultaneous Association Discovery and Diagnosis of Alzheimer's Disease.

Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Nystrom Approximation for Sparse Kernel Methods: Theoretical Analysis and Empirical Evaluation.

Zenglin Xu, Rong Jin, Bin Shen, Shenghuo Zhu

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Joint Association Discovery and Diagnosis of Alzheimer's Disease by Supervised Heterogeneous Multiview Learning.

Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu

Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

Non-monotonic Feature Selection for Regression.

Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu

Proceedings of the Neural Information Processing - 21st International Conference, 2014

Kernel tapering: A simple and effective approach to sparse kernels for image processing.

Bin Shen, Zenglin Xu, Jan P. Allebach

Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

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

Proceedings of the Computer Security - ESORICS 2014, 2014

2013

Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis

Shandian Zhe, Zenglin Xu, Yuan Qi, Peng Yu

CoRR, 2013

Exact and Stable Recovery of Pairwise Interaction Tensors.

Shouyuan Chen, Michael R. Lyu, Irwin King, Zenglin Xu

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis.

Zenglin Xu, Feng Yan, Yuan (Alan) Qi

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Efficient Sparse Generalized Multiple Kernel Learning.

Haiqin Yang, Zenglin Xu, Jieping Ye, Irwin King, Michael R. Lyu

IEEE Trans. Neural Networks, 2011

InfTucker: t-Process based Infinite Tensor Decomposition

Zenglin Xu, Feng Yan, Yuan (Alan) Qi

CoRR, 2011

Sparse matrix-variate Gaussian process blockmodels for network modeling.

Feng Yan, Zenglin Xu, Yuan (Alan) Qi

Proceedings of the UAI 2011, 2011

Sparse Matrix-Variate t Process Blockmodels.

Zenglin Xu, Feng Yan, Yuan (Alan) Qi

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Discriminative semi-supervised feature selection via manifold regularization.

Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin

IEEE Trans. Neural Networks, 2010

Robust Metric Learning by Smooth Optimization.

Kaizhu Huang, Rong Jin, Zenglin Xu, Cheng-Lin Liu

Proceedings of the UAI 2010, 2010

Online Learning for Group Lasso.

Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Simple and Efficient Multiple Kernel Learning by Group Lasso.

Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Smooth Optimization for Effective Multiple Kernel Learning.

Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu, Irwin King

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

A novel kernel-based maximum a posteriori classification method.

Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu

Neural Networks, 2009

Heavy-Tailed Symmetric Stochastic Neighbor Embedding.

Zhirong Yang, Irwin King, Zenglin Xu, Erkki Oja

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Adaptive Regularization for Transductive Support Vector Machine.

Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, Zhirong Yang

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Supervised Self-taught Learning: Actively transferring knowledge from unlabeled data.

Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Colin Campbell

Proceedings of the International Joint Conference on Neural Networks, 2009

Non-monotonic feature selection.

Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

An Extended Level Method for Efficient Multiple Kernel Learning.

Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Semi-supervised Learning from General Unlabeled Data.

Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

An Effective Approach to 3D Deformable Surface Tracking.

Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu

Proceedings of the Computer Vision, 2008

Semi-supervised text categorization by active search.

Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu, Irwin King

Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008

2007

Feature Selection Based on Minimum Error minimax Probability Machine.

Zenglin Xu, Irwin King, Michael R. Lyu

Int. J. Pattern Recognit. Artif. Intell., 2007

Web page classification with heterogeneous data fusion.

Zenglin Xu, Irwin King, Michael R. Lyu

Proceedings of the 16th International Conference on World Wide Web, 2007

Efficient Convex Relaxation for Transductive Support Vector Machine.

Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Maximum Margin based Semi-supervised Spectral Kernel Learning.

Zenglin Xu, Jianke Zhu, Michael R. Lyu, Irwin King

Proceedings of the International Joint Conference on Neural Networks, 2007

Kernel Maximum a Posteriori Classification with Error Bound Analysis.

Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu

Proceedings of the Neural Information Processing, 14th International Conference, 2007

2004

Feature Selection with Particle Swarms.

Yu Liu, Zheng Qin, Zenglin Xu, Xingshi He

Proceedings of the Computational and Information Science, First International Symposium, 2004