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Computer Science
China
2025

Research.com Recognitions

  • 2025 - Research.com Computer Science in China Leader Award

Overview

Jieping Ye is affiliated with Alibaba Group (China) and has made contributions primarily in the fields of Computer Science and Engineering. Their research spans a range of topics including Artificial Intelligence, Computer Vision and Pattern Recognition, Transportation, Automotive Engineering, and Building and Construction.

Their work integrates several specialized themes such as Transportation and Mobility Innovations, Transportation Planning and Optimization, Advanced Neural Network Applications, Domain Adaptation and Few-Shot Learning, Sharing Economy and Platforms, Traffic Prediction and Management Techniques, and Topic Modeling.

Frequent coauthors in Jieping Ye's research include:

  • Hongtu Zhu
  • Zhiwei Qin
  • Yuhong Guo
  • Shuang Qiu
  • Deyi Ji

Jieping Ye has published extensively in the following venues:

  • arXiv (Cornell University)
  • Transportation Research Part C Emerging Technologies
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Image Processing
  • bioRxiv (Cold Spring Harbor Laboratory)

Notable recent papers include:

  • Object Detection in 20 Years: A Survey (2023), Proceedings of the IEEE
  • A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications (2021), IEEE Transactions on Knowledge and Data Engineering
  • A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications (2020), arXiv (Cornell University)
  • Pricing and equilibrium in on-demand ride-pooling markets (2020), Transportation Research Part B Methodological
  • An Attention-Based Graph Neural Network for Heterogeneous Structural Learning (2020), Proceedings of the AAAI Conference on Artificial Intelligence

Jieping Ye has authored a book titled Reinforcement Learning in the Ridesharing Marketplace published by Morgan & Claypool Publishers in 2024.

Best Publications

  • Object Detection in 20 Years: A Survey

    Unknown

  • Tensor completion for estimating missing values in visual data

    Ji Liu;Przemyslaw Musialski;Peter Wonka;Jieping Ye

  • A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

    Jie Gui;Zhenan Sun;Yonggang Wen;Dacheng Tao

  • Fast and Accurate Matrix Completion via Truncated Nuclear Norm Regularization

    Yao Hu;Debing Zhang;Jieping Ye;Xuelong Li

  • Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting

    Xu Geng;Yaguang Li;Leye Wang;Lingyu Zhang

  • Object Detection in 20 Years: A Survey

    Zhengxia Zou;Zhenwei Shi;Yuhong Guo;Jieping Ye

  • Generalized Low Rank Approximations of Matrices

    Unknown

  • An accelerated gradient method for trace norm minimization

    Shuiwang Ji;Jieping Ye

  • Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation.

    Shuai Huang;Jing Li;Liang Sun;Jieping Ye

  • On Similarity Preserving Feature Selection

    Zheng Zhao;Lei Wang;Huan Liu;Jieping Ye

  • Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis

    Liang Sun;Shuiwang Ji;Jieping Ye

  • An optimization criterion for generalized discriminant analysis on undersampled problems

    Jieping Ye;R. Janardan;C.H. Park;H. Park

  • Least squares linear discriminant analysis

    Jieping Ye

  • Robust multi-task feature learning

    Pinghua Gong;Jieping Ye;Changshui Zhang

  • A two-stage linear discriminant analysis via QR-decomposition

    Unknown

  • A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems

    Pinghua Gong;Changshui Zhang;Zhaosong Lu;Jianhua Huang

  • Efficient Methods for Overlapping Group Lasso

    Lei Yuan;Jun Liu;Jieping Ye

  • The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms

    Yongxin Tong;Yuqiang Chen;Zimu Zhou;Lei Chen

  • Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis

    Wenlu Zhang;Rongjian Li;Tao Zeng;Qian Sun

  • Hypergraph spectral learning for multi-label classification

    Liang Sun;Shuiwang Ji;Jieping Ye

  • Integrating low-rank and group-sparse structures for robust multi-task learning

    Jianhui Chen;Jiayu Zhou;Jieping Ye

  • A multi-task learning formulation for predicting disease progression

    Jiayu Zhou;Lei Yuan;Jun Liu;Jieping Ye

  • Multi-task Representation Learning for Travel Time Estimation

    Yaguang Li;Kun Fu;Zheng Wang;Cyrus Shahabi

Frequent Co-Authors

Paul M. Thompson
Paul M. Thompson University of Southern California
Eric M. Reiman
Eric M. Reiman Arizona State University
Tianming Liu
Tianming Liu University of Georgia
Peter Wonka
Peter Wonka King Abdullah University of Science and Technology
Jian Tang
Jian Tang Syracuse University
Naren Ramakrishnan
Naren Ramakrishnan Virginia Tech
Jiayu Zhou
Jiayu Zhou Michigan State University
Zhenwei Shi
Zhenwei Shi Beihang University
Hai Yang
Hai Yang Hong Kong University of Science and Technology
Chang-Tien Lu
Chang-Tien Lu Virginia Tech

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