World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
10922
World Ranking
4599
National Ranking
616

Overview

Zenglin Xu is affiliated with the Harbin Institute of Technology in China and has an extensive publication record in the field of Computer Science. Their research contributions primarily focus on Artificial Intelligence, with notable work in Computer Vision and Pattern Recognition as well as Information Systems, Electrical and Electronic Engineering, and Signal Processing.

The scientist's research topics cover a broad range of areas including:

  • Domain Adaptation and Few-Shot Learning
  • Privacy-Preserving Technologies in Data
  • Topic Modeling
  • Face and Expression Recognition
  • Natural Language Processing Techniques
  • Advanced Graph Neural Networks
  • Multimodal Machine Learning Applications

Zenglin Xu has published extensively in recognized venues. The most frequent publication platforms include:

  • arXiv (Cornell University)
  • Neural Networks
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Neurocomputing
  • IEEE Transactions on Knowledge and Data Engineering

Some of the recent papers provide insight into the areas of deep semi-supervised learning, multi-view clustering, and graph-based learning methodologies. Notable examples include:

  • "A Survey on Deep Semi-Supervised Learning" (2022), published in IEEE Transactions on Knowledge and Data Engineering
  • "Large-Scale Multi-View Subspace Clustering in Linear Time" (2020), published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Graph-Based Semi-Supervised Learning: A Comprehensive Review" (2022), published in IEEE Transactions on Neural Networks and Learning Systems
  • "Deep embedded multi-view clustering with collaborative training" (2021), published in Information Sciences
  • "Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-View Clustering" (2021), published in IEEE Transactions on Knowledge and Data Engineering

The scientist frequently collaborates with several co-authors, indicating active research partnerships. Key co-authors include:

  • Irwin King
  • Dun Zeng
  • Yazhou Ren
  • Zhao Kang
  • Shudong Huang

Best Publications

  • A Survey on Deep Semi-Supervised Learning

    Unknown

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

    Zhao Kang;Wangtao Zhou;Zhitong Zhao;Junming Shao

  • Discriminative Semi-Supervised Feature Selection Via Manifold Regularization

    Zenglin Xu;Irwin King;Michael Rung-Tsong Lyu;Rong Jin

  • Simple and Efficient Multiple Kernel Learning by Group Lasso

    Zenglin Xu;Rong Jin;Haiqin Yang;Irwin King

  • Graph-based Semi-supervised Learning: A Comprehensive Review.

    Zixing Song;Xiangli Yang;Zenglin Xu;Irwin King

  • Robust Graph Learning From Noisy Data

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

  • Multi-graph fusion for multi-view spectral clustering

    Zhao Kang;Guoxin Shi;Shudong Huang;Wenyu Chen

  • Partition level multiview subspace clustering.

    Zhao Kang;Xinjia Zhao;Chong Peng;Hongyuan Zhu

  • Pseudo-Supervised Deep Subspace Clustering

    Juncheng Lv;Zhao Kang;Xiao Lu;Zenglin Xu

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

    Linnan Wang;Jinmian Ye;Yiyang Zhao;Wei Wu

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

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

  • Deep embedded multi-view clustering with collaborative training

    Jie Xu;Yazhou Ren;Guofeng Li;Lili Pan

  • An Extended Level Method for Efficient Multiple Kernel Learning

    Zenglin Xu;Rong Jin;Irwin King;Michael Lyu

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

    Shudong Huang;Zhao Kang;Zenglin Xu

  • Semi-supervised deep embedded clustering

    Yazhou Ren;Kangrong Hu;Xinyi Dai;Lili Pan

  • Low-rank Kernel Learning for Graph-based Clustering

    Zhao Kang;Liangjian Wen;Wenyu Chen;Zenglin Xu

  • Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-view Clustering

    Shudong Huang;Ivor Tsang;Zenglin Xu;Jian Cheng Lv

  • RegNet: Self-Regulated Network for Image Classification.

    Jing Xu;Yu Pan;Xinglin Pan;Steven C. H. Hoi

  • Structured graph learning for clustering and semi-supervised classification

    Zhao Kang;Chong Peng;Qiang Cheng;Xinwang Liu

  • Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition

    Jinmian Ye;Linnan Wang;Guangxi Li;Di Chen

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

    Zenglin Xu;Feng Yan;Alan Qi

  • Online Learning for Group Lasso

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

  • Discriminative semi-supervised feature selection via manifold regularization

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

Frequent Co-Authors

Zhao Kang
Zhao Kang University of Electronic Science and Technology of China
Irwin King
Irwin King Chinese University of Hong Kong
Michael R. Lyu
Michael R. Lyu Chinese University of Hong Kong
Kaizhu Huang
Kaizhu Huang Duke Kunshan University
Rong Jin
Rong Jin Alibaba Group (China)
Steven C. H. Hoi
Steven C. H. Hoi Alibaba Group (China)
Jianke Zhu
Jianke Zhu Zhejiang University
Gerard de Melo
Gerard de Melo Hasso Plattner Institute
Ivor W. Tsang
Ivor W. Tsang Agency for Science, Technology and Research
Lingxi Xie
Lingxi Xie Huawei Technologies (China)

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