World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
11533
World Ranking
6727
National Ranking
2968

Overview

Victor S. Sheng is affiliated with Texas Tech University in the United States. Their research primarily spans the field of Computer Science, with a significant focus on Artificial Intelligence.

The scientist's work covers several subfields within Computer Science, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications

The main research topics addressed in their publications include:

  • Recommender Systems and Techniques
  • Topic Modeling
  • Advanced Graph Neural Networks
  • Advanced Neural Network Applications
  • Network Security and Intrusion Detection
  • Text and Document Classification Technologies
  • Mobile Crowdsensing and Crowdsourcing

Victor S. Sheng has contributed frequently to notable publication venues, among them:

  • arXiv (Cornell University)
  • Expert Systems with Applications
  • Computers, materials & continua
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering

Recent papers authored or coauthored by Sheng include:

  • "Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation" (2020), published in IEEE Transactions on Knowledge and Data Engineering
  • "Deep semi-supervised learning for medical image segmentation: A review" (2024), published in Expert Systems with Applications
  • "Long- and short-term self-attention network for sequential recommendation" (2020), published in Neurocomputing
  • "Multi-Label Active Learning Algorithms for Image Classification" (2020), published in ACM Computing Surveys
  • "Loss Functions of Generative Adversarial Networks (GANs): Opportunities and Challenges" (2020), published in IEEE Transactions on Emerging Topics in Computational Intelligence

Frequent collaborators in Sheng's work include:

  • Pengpeng Zhao
  • Wei Fang
  • Guanfeng Liu
  • Jieren Cheng
  • Yanchi Liu

In addition to journal and conference publications, Victor S. Sheng has published a book titled "Big Data and Security" in 2022 through Springer Science+Business Media.

Best Publications

  • Get another label? improving data quality and data mining using multiple, noisy labelers

    Victor S. Sheng;Foster Provost;Panagiotis G. Ipeirotis

  • Incremental Support Vector Learning for Ordinal Regression

    Bin Gu;Victor S. Sheng;Keng Yeow Tay;Walter Romano

  • Graph contextualized self-attention network for session-based recommendation

    Chengfeng Xu;Pengpeng Zhao;Yanchi Liu;Victor S. Sheng

  • Incremental learning for ν -Support Vector Regression

    Bin Gu;Victor S. Sheng;Zhijie Wang;Derek Ho

  • A Robust Regularization Path Algorithm for $ u $ -Support Vector Classification

    Bin Gu;Victor S. Sheng

  • Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation

    Pengpeng Zhao;Anjing Luo;Yanchi Liu;Fuzhen Zhuang

  • Structural Minimax Probability Machine

    Bin Gu;Xingming Sun;Victor S. Sheng

  • Feature-level Deeper Self-Attention Network for Sequential Recommendation

    Tingting Zhang;Pengpeng Zhao;Yanchi Liu;Victor S. Sheng

  • A Comparative Study of SIFT and its Variants

    Jian Wu;Zhiming Cui;Victor S. Sheng;Pengpeng Zhao

  • Cost-Sensitive Learning and the Class Imbalance Problem

    Charles X. Ling;Victor S. Sheng

  • Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation

    Pengpeng Zhao;Haifeng Zhu;Yanchi Liu;Jiajie Xu

  • Repeated labeling using multiple noisy labelers

    Panagiotis G. Ipeirotis;Foster Provost;Victor S. Sheng;Jing Wang

  • A method for improving CNN-based image recognition using DCGAN

    Wei Fang;Wei Fang;Feihong Zhang;Victor S. Sheng;Yewen Ding

  • Thresholding for making classifiers cost-sensitive

    Victor S. Sheng;Charles X. Ling

  • Test strategies for cost-sensitive decision trees

    C.X. Ling;V.S. Sheng;Q. Yang

  • Learning from crowdsourced labeled data: a survey

    Jing Zhang;Xindong Wu;Victor S. Sheng

  • Liver CT sequence segmentation based with improved U-Net and graph cut

    Zhe Liu;Yu-Qing Song;Victor S. Sheng;Liangmin Wang

  • Cost-Sensitive Learning.

    Charles X. Ling;Victor S. Sheng

  • Recurrent Convolutional Neural Network for Sequential Recommendation

    Chengfeng Xu;Pengpeng Zhao;Yanchi Liu;Jiajie Xu

  • An abnormal network flow feature sequence prediction approach for DDoS attacks detection in big data environment

    Renjie Cheng;Ruomeng Xu;Xiangyan Tang;Victor S Sheng

Frequent Co-Authors

Charles X. Ling
Charles X. Ling University of Western Ontario
Xindong Wu
Xindong Wu Hefei University of Technology
Fuzhen Zhuang
Fuzhen Zhuang Beihang University
Xiaofang Zhou
Xiaofang Zhou Hong Kong University of Science and Technology
Guanfeng Liu
Guanfeng Liu Macquarie University
An Liu
An Liu Soochow University
Panagiotis G. Ipeirotis
Panagiotis G. Ipeirotis New York University
Foster Provost
Foster Provost New York University
Shuo Li
Shuo Li Case Western Reserve University
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey

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