Publications (Google Scholar Profile)

2022

  • Non-IID Federated Learning with Sharper Risk Bound.
    Bojian Wei, Jian Li*, Yong Liu, Weiping Wang. IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
    [PDF]

  • Convolutional Spectral Kernel Learning with Generalization Guarantees.
    Jian Li, Yong Liu, Weiping Wang. Artificial Intelligence (AI).
    [Free Access before Dec 1, 2022] [PDF] [Code]

  • Sharper Utility Bounds for Differentially Private Models: Smooth and Non-smooth.
    Yilin Kang, Yong Liu, Jian Li, Weiping Wang. The Conference on Information and Knowledge Management (CIKM 2022).
    [PDF]

  • Non-IID Distributed Learning with Optimal Mixture Weights.
    Jian Li, Bojian Wei, Yong Liu, Weiping Wang. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. (ECML-PKDD 2022).
    [PDF]

  • Ridgeless Regression with Random Features.
    Jian Li, Yong Liu, Yingying Zhang. The 31st International Joint Conference on Artificial Intelligence. (IJCAI 2022).
    [PDF] [Code]

2021

  • Operation-level Progressive Differentiable Architecture Search.
    Bojian Wei, Jian Li*, Yong Liu, Weiping Wang. Pacific Rim International Conference on Artificial Intelligence (PRICAI 2021).
    [PDF] [Presentation] [Best student paper award]
  • Operation-level Progressive Differentiable Architecture Search.
    Xunyu Zhu, Jian Li*, Yong Liu, Weiping Wang. 2021 IEEE International Conference on Data Mining (ICDM 2021), 1559-1564.
    [PDF]

2020

  • Neural Architecture Optimization with Graph VAE. Preprint.
    Jian Li, Yong Liu, Weiping Wang. arXiv preprint arXiv:2006.10310, 2020.
    [PDF] [Code]
  • Convolutional Spectral Kernel Learning. Preprint.
    Jian Li, Yong Liu, Weiping Wang. arXiv preprint arXiv:2002.12744, 2020.
    [PDF] [Code]
  • Automated Spectral Kernel Learning.
    Jian Li, Yong Liu, Weiping Wang. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), 4618-4625.
    [PDF] [Poster] [Code]

2019

  • Multi-Class Learning using Unlabeled Samples: Theory and Algorithm.
    Jian Li, Yong Liu, Rong Yin, Weiping Wang. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019).
    [PDF] [Poster] [Slides] [Code]
  • Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis.
    Jian Li, Yong Liu, Rong Yin, Weiping Wang. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019).
    [PDF] [Poster] [Slides] [Code]
  • Learning Vector-valued Functions with Local Rademacher Complexity. Preprint.
    Jian Li, Yong Liu, Weiping Wang. arXiv preprint arXiv:1909.04883, 2019.
    [PDF] [Code]
  • Distributed Learning with Random Features. Preprint.
    Jian Li, Yong Liu, Weiping Wang. arXiv preprint arXiv:1906.03155, 2019.
    [PDF] [Code]
  • Efficient Cross-Validation for Semi-Supervised Learning. Preprint.
    Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang. arXiv preprint arXiv:1902.04768, 2019.
    [PDF]

2018

  • Multi-Class Learning: From Theory to Algorithm.
    Jian Li, Yong Liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang. Advances in Neural Information Processing Systems 31 (NeurIPS 2018).
    [PDF] [Poster] [Sildes] [3-minute video] [Code]
  • Max-Diversity Distributed Learning: Theory and Algorithms. Preprint.
    Yong Liu, Jian Li, Weiping Wang. arXiv preprint arXiv:1812.07738, 2018.
    [PDF] [Code]

2017

  • Efficient Kernel Selection via Spectral Analysis.
    Jian Li, Yong Liu, Hailun Lin, Yinliang Yue, Weiping Wang. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017) .
    [PDF] [Poster] [Sildes]