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Yongfeng Huang

Yongfeng Huang

D-Index & Metrics

Computer Science

D-Index
53
Citations
9310
World Ranking
4898
National Ranking
657

Overview

Yongfeng Huang is affiliated with Tsinghua University in China and has contributed extensively to the field of computer science, with a primary focus on artificial intelligence. Their research spans several subfields, including computer vision and pattern recognition, information systems, electrical and electronic engineering, and computer networks and communications.

The scientist's work addresses core topics such as topic modeling, recommender systems and techniques, advanced steganography and watermarking techniques, natural language processing techniques, internet traffic analysis and secure e-voting, advanced graph neural networks, and privacy-preserving technologies in data.

Yongfeng Huang has published numerous papers in multiple venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Knowledge-Based Systems
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • IEEE Transactions on Information Forensics and Security
  • SSRN Electronic Journal

Recent research papers associated with Yongfeng Huang include:

  • "Communication-efficient federated learning via knowledge distillation" (2022, Nature Communications)
  • "A federated graph neural network framework for privacy-preserving personalization" (2022, Nature Communications)
  • "β-MnO2 with proton conversion mechanism in rechargeable zinc ion battery" (2020, Journal of Energy Chemistry)
  • "VAE-Stega: Linguistic Steganography Based on Variational Auto-Encoder" (2020, IEEE Transactions on Information Forensics and Security)
  • "Personalized News Recommendation: Methods and Challenges" (2022, ACM Transactions on Information Systems)

Yongfeng Huang frequently collaborates with a group of coauthors. The most frequent collaborators are:

  • Chuhan Wu
  • Fangzhao Wu
  • Tao Qi
  • Xing Xie
  • Zhongliang Yang

Their publications collectively contribute to a comprehensive understanding of the development and application of federated learning, graph neural networks, steganography, and recommendation systems, among other areas within computer science.

Best Publications

  • Neural News Recommendation with Multi-Head Self-Attention.

    Chuhan Wu;Fangzhao Wu;Suyu Ge;Tao Qi

  • RNN-Stega: Linguistic Steganography Based on Recurrent Neural Networks

    Zhong-Liang Yang;Xiao-Qing Guo;Zi-Ming Chen;Yong-Feng Huang

  • NPA: Neural News Recommendation with Personalized Attention

    Chuhan Wu;Fangzhao Wu;Mingxiao An;Jianqiang Huang

  • Dynamic-Hash-Table Based Public Auditing for Secure Cloud Storage

    Hui Tian;Yuxiang Chen;Chin-Chen Chang;Hong Jiang

  • Neural News Recommendation with Attentive Multi-View Learning.

    Chuhan Wu;Fangzhao Wu;Mingxiao An;Jianqiang Huang

  • TS-RNN: Text Steganalysis Based on Recurrent Neural Networks

    Zhongliang Yang;Ke Wang;Jian Li;Yongfeng Huang

  • Steganography in Inactive Frames of VoIP Streams Encoded by Source Codec

    Yong Feng Huang;Shanyu Tang;Jian Yuan

  • VAE-Stega: Linguistic Steganography Based on Variational Auto-Encoder

    Zhong-Liang Yang;Si-Yu Zhang;Yu-Ting Hu;Zhi-Wen Hu

  • Steganography Integration Into a Low-Bit Rate Speech Codec

    Yongfeng Huang;Chenghao Liu;Shanyu Tang;Sen Bai

  • Empowering News Recommendation with Pre-trained Language Models

    Chuhan Wu;Fangzhao Wu;Tao Qi;Yongfeng Huang

  • Privacy-Preserving News Recommendation Model Learning

    Tao Qi;Fangzhao Wu;Chuhan Wu;Yongfeng Huang

  • Neural Chinese Named Entity Recognition via CNN-LSTM-CRF and Joint Training with Word Segmentation

    Fangzhao Wu;Junxin Liu;Chuhan Wu;Yongfeng Huang

  • FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation.

    Chuhan Wu;Fangzhao Wu;Yang Cao;Yongfeng Huang

  • Graph Enhanced Representation Learning for News Recommendation

    Suyu Ge;Chuhan Wu;Fangzhao Wu;Tao Qi

  • A hybrid unsupervised method for aspect term and opinion target extraction

    Chuhan Wu;Fangzhao Wu;Sixing Wu;Zhigang Yuan

  • A Blockchain-based access control scheme with multiple attribute authorities for secure cloud data sharing

    Xuanmei Qin;Yongfeng Huang;Zhen Yang;Xing Li

  • Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network

    Zhongliang Yang;Yongfeng Huang;Yiran Jiang;Yuxi Sun

  • RNN-SM: Fast Steganalysis of VoIP Streams Using Recurrent Neural Network

    Zinan Lin;Yongfeng Huang;Jilong Wang

  • Neural News Recommendation with Topic-Aware News Representation.

    Chuhan Wu;Fangzhao Wu;Mingxiao An;Yongfeng Huang

  • Fairness-aware News Recommendation with Decomposed Adversarial Learning.

    Chuhan Wu;Fangzhao Wu;Xiting Wang;Yongfeng Huang

  • Towards building a high-quality microblog-specific Chinese sentiment lexicon

    Fangzhao Wu;Yongfeng Huang;Yangqiu Song;Shixia Liu

  • Privacy-preserving public auditing for secure data storage in fog-to-cloud computing

    Hui Tian;Fulin Nan;Chin-Chen Chang;Yongfeng Huang

  • Unsupervised pre-trained filter learning approach for efficient convolution neural network

    Sadaqat ur Rehman;Shanshan Tu;Muhammad Waqas;Yongfeng Huang

  • Optimization of CNN through Novel Training Strategy for Visual Classification Problems.

    Sadaqat Ur Rehman;Shanshan Tu;Obaid Ur Rehman;Yongfeng Huang

  • CSFL: A novel unsupervised convolution neural network approach for visual pattern classification

    Sadaqat ur Rehman;Shanshan Tu;Yongfeng Huang;Guojie Liu

Frequent Co-Authors

Xing Xie
Xing Xie Microsoft Research Asia (China)
Yu-Jin Zhang
Yu-Jin Zhang Tsinghua University
Chin-Chen Chang
Chin-Chen Chang Feng Chia University
Yangqiu Song
Yangqiu Song Hong Kong University of Science and Technology
Tian Wang
Tian Wang Beijing Normal University
Liang Zheng
Liang Zheng Australian National University
Shixia Liu
Shixia Liu Tsinghua University
Jun Yan
Jun Yan Microsoft (United States)
Suhang Wang
Suhang Wang Pennsylvania State University
Jie Liu
Jie Liu Duke University

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