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]