Publications (Google Scholar Profile)

2023

• Optimal Convergence Rates for Distributed Nyström Approximation. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  Journal of Machine Learning Research (JMLR), 2023. CCF-A journal.

• Optimal Convergence Rates for Agnostic Nyström Kernel Learning. [pdf]
  Jian Li, Yong Liu, Weiping Wang.
  International Conference on Machine Learning (ICML), 2023. CCF-A conference.

• Towards Sharp Analysis for Distributed Learning with Random Features. [pdf]
  Jian Li, Yong Liu.
  International Joint Conference on Artificial Intelligence (IJCAI), 2023. CCF-A conference.

• Optimal Convergence for Agnostic Kernel Learning With Random Features. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. CCF-B journal.

• Semi-supervised vector-valued learning: Improved bounds and algorithms. [pdf]
  Jian Li, Yong Liu, Weiping Wang.
  Pattern Recognition (PR), 2023. CCF-B journal.

• Improving Differentiable Architecture Search via Self-distillation. [pdf]
  Xunyu Zhu, Jian Li*, Yong Liu, Weiping Wang.
  Neural Networks, 2023. CCF-B journal.

• Towards Sharper Risk Bounds for Agnostic Multi-Objectives Learning. [pdf]
  Bojian Wei, Jian Li*, Yong Liu, Weiping Wang.
  International Joint Conference on Neural Networks (IJCNN), 2023. CCF-C conference.

• Data Heterogeneity Differential Privacy: From Theory to Algorithm. [pdf]
  Yiling Kang, Jian Li*, Yong Liu, Weiping Wang.
  International Conference on Computational Science (ICCS), 2023.

• A Survey on Model Compression for Large Language Models. [pdf]
  Xunyu Zhu, Jian Li*, Yong Liu, Can Ma, Weiping Wang.
  arXiv:2308.07633.

• Robust Neural Architecture Search. [pdf]
  Xunyu Zhu, Jian Li*, Yong Liu, Weiping Wang.
  arXiv:2304.02845.

2022

• Convolutional Spectral Kernel Learning with Generalization Guarantees. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  Artificial Intelligence (AIJ), 2022. CCF-A journal.

• Ridgeless Regression with Random Features. [pdf] [code]
  Jian Li, Yong Liu, Yingying Zhang.
  International Joint Conference on Artificial Intelligence (IJCAI), 2022. CCF-A conference.

• Non-IID Distributed Learning with Optimal Mixture Weights. [pdf]
  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. CCF-B conference.

• Non-IID Federated Learning with Sharper Risk Bound. [pdf]
  Bojian Wei, Jian Li*, Yong Liu, Weiping Wang.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022. CCF-B journal.

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

2021

• Federated learning for non-iid data: From theory to algorithm. [pdf] [presentation] [🏆Best student paper award]
  Bojian Wei, Jian Li*, Yong Liu, Weiping Wang.
  Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2021. CCF-C conference.

• Operation-level Progressive Differentiable Architecture Search. [pdf]
  Xunyu Zhu, Jian Li*, Yong Liu, Weiping Wang.
  International Conference on Data Mining (ICDM), 2021. CCF-B conference.

2020

• Automated Spectral Kernel Learning. [pdf] [poster] [code]
  Jian Li, Yong Liu, Weiping Wang.
  AAAI Conference on Artificial Intelligence (AAAI), 2020. CCF-A conference.

• Neural Architecture Optimization with Graph VAE. [pdf] [code]
  Jian Li, Yong Liu, Weiping Wang.
  arXiv preprint arXiv:2006.10310, 2020.

2019

• Multi-Class Learning using Unlabeled Samples: Theory and Algorithm. [pdf] [poster] [slides] [code]
  Jian Li, Yong Liu, Rong Yin, Weiping Wang.
  International Joint Conference on Artificial Intelligence (IJCAI), 2019. CCF-A conference.

• Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis. g[pdf] [poster] [slides] [code]
  Jian Li, Yong Liu, Rong Yin, Weiping Wang.
  International Joint Conference on Artificial Intelligence (IJCAI), 2019. CCF-A conference.

• Efficient Cross-Validation for Semi-Supervised Learning. [pdf]
  Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang.
  arXiv preprint arXiv:1902.04768, 2019.

2018

• Multi-Class Learning: From Theory to Algorithm. [pdf] [poster] [sildes] [3-minute video] [code]
  Jian Li, Yong Liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang.
  Advances in Neural Information Processing Systems 31 (NeurIPS), 2018. CCF-A conference.

• Max-Diversity Distributed Learning: Theory and Algorithms. [pdf] [code]
  Yong Liu, Jian Li, Weiping Wang.
  arXiv preprint arXiv:1812.07738, 2018.

2017

• Efficient Kernel Selection via Spectral Analysis. [pdf] [poster] [sildes]
  Jian Li, Yong Liu, Hailun Lin, Yinliang Yue, Weiping Wang.
  International Joint Conference on Artificial Intelligence (IJCAI), 2017. CCF-A conference.