World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
9910
World Ranking
8248
National Ranking
1080

Overview

Yingjie Tian is affiliated with the University of Chinese Academy of Sciences in China and has contributed extensively to research in computer science and engineering. Their primary areas of study include artificial intelligence, computer vision and pattern recognition, electrical and electronic engineering, civil and structural engineering, and control and systems engineering.

The main research themes covered in Tian's work include:

  • Face and Expression Recognition
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Text and Document Classification Technologies
  • Advanced Neural Network Applications
  • Anomaly Detection Techniques and Applications
  • Energy Load and Power Forecasting

Tian has published papers in various journals and conferences, reflecting a focus on machine learning theory and applications, as well as advanced neural networks. Frequent publication venues consist of:

  • Neural Networks
  • SSRN Electronic Journal
  • arXiv (Cornell University)
  • Neurocomputing
  • Information Fusion

Recent notable publications by Yingjie Tian include:

  • A comprehensive survey on regularization strategies in machine learning, 2021, Information Fusion
  • Recent Advances in Stochastic Gradient Descent in Deep Learning, 2023, Mathematics
  • Meta-learning approaches for learning-to-learn in deep learning: A survey, 2022, Neurocomputing

Other well-cited works related to machine learning, although led by different authors, also underline the scientific context within which Tian operates, such as surveys on loss functions and applications of machine learning in waste treatment processes.

Yingjie Tian frequently collaborates with several researchers, including:

  • Saiji Fu
  • Jingjing Tang
  • Zhiquan Qi
  • Yuqi Zhang
  • Yong Shi

The breadth of Tian's publication record covers 247 works in computer science and 114 in engineering, with significant contributions oriented towards artificial intelligence and machine learning subfields. Their research intersects theoretical and applied domains, especially in face recognition, domain adaptation, and data classification.

Best Publications

  • A Comprehensive Survey of Clustering Algorithms

    Dongkuan Xu;Yingjie Tian

  • A Comprehensive Survey of Loss Functions in Machine Learning

    Qi Wang;Yue Ma;Kun Zhao;Yingjie Tian

  • Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions

    Naiyang Deng;Yingjie Tian;Chunhua Zhang

  • Robust twin support vector machine for pattern classification

    Zhiquan Qi;Yingjie Tian;Yong Shi

  • A comprehensive survey on regularization strategies in machine learning

    Unknown

  • Optimization Based Data Mining: Theory and Applications

    Yong Shi;Yingjie Tian;Gang Kou;Yi Peng

  • Credit card churn forecasting by logistic regression and decision tree

    Guangli Nie;Wei Rowe;Lingling Zhang;Yingjie Tian

  • Nonparallel Support Vector Machines for Pattern Classification

    Yingjie Tian;Zhiquan Qi;Xuchan Ju;Yong Shi

  • An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization

    Seyed Mojtaba Hosseini Bamakan;Huadong Wang;Tian Yingjie;Yong Shi

  • Laplacian twin support vector machine for semi-supervised classification

    Zhiquan Qi;Yingjie Tian;Yong Shi

  • Recent advances on support vector machines research

    Yingjie Tian;Yong Shi;Xiaohui Liu

  • Twin support vector machine with Universum data

    Zhiquan Qi;Yingjie Tian;Yong Shi

  • Structural twin support vector machine for classification

    Zhiquan Qi;Yingjie Tian;Yong Shi

  • Network Intrusion Detection

    Yong Shi;Yong Shi;Yingjie Tian;Gang Kou;Yi Peng

  • Multiview Privileged Support Vector Machines

    Jingjing Tang;Yingjie Tian;Peng Zhang;Xiaohui Liu

  • Support vector machine classifier with truncated pinball loss

    Xin Shen;Lingfeng Niu;Zhiquan Qi;Yingjie Tian

  • Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification.

    Guoqiang Wu;Ruobing Zheng;Yingjie Tian;Dalian Liu

  • Ramp loss one-class support vector machine; A robust and effective approach to anomaly detection problems

    Yingjie Tian;Mahboubeh Mirzabagheri;Seyed Mojtaba Hosseini Bamakan;Huadong Wang

  • Survey and experimental study on metric learning methods.

    Dewei Li;Yingjie Tian

  • Predicting DNA- and RNA-binding proteins from sequences with kernel methods.

    Xiaojian Shao;Yingjie Tian;Lingyun Wu;Yong Wang

  • When Ensemble Learning Meets Deep Learning

    Zhiquan Qi;Bo Wang;Yingjie Tian;Peng Zhang

Frequent Co-Authors

Yong Shi
Yong Shi Chinese Academy of Sciences
Gang Kou
Gang Kou Southwestern University of Finance and Economics
Yi Peng
Yi Peng University of Electronic Science and Technology of China
Peng Zhang
Peng Zhang Huazhong University of Science and Technology
Nai-Yang Deng
Nai-Yang Deng China Agricultural University
Xiaohui Liu
Xiaohui Liu Brunel University London
Jia Wu
Jia Wu Macquarie University
Qi Wang
Qi Wang Northwestern Polytechnical University
Panos M. Pardalos
Panos M. Pardalos University of Florida
Chengqi Zhang
Chengqi Zhang Hong Kong Polytechnic University

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