Jian Li

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 24

Top Topics

Manifold Regularization

Dirichlet Prior

Semidefinite Program

Differentially Private

Top Venues

IEEE Trans. Inf. Theory

Publications

Xunyu Zhu, Jian Li, Can Ma, Weiping Wang
Key-Point-Driven Mathematical Reasoning Distillation of Large Language Model. CoRR (2024)
Jian Li, Yong Liu, Weiping Wang
Optimal Rates for Agnostic Distributed Learning. IEEE Trans. Inf. Theory 70 (4) (2024)
Bojian Wei, Jian Li, Yong Liu, Weiping Wang
Non-IID Federated Learning With Sharper Risk Bound. IEEE Trans. Neural Networks Learn. Syst. 35 (5) (2024)
Yilin Kang, Jian Li, Yong Liu, Weiping Wang
Data Heterogeneity Differential Privacy: From Theory to Algorithm. ICCS (1) (2023)
Jian Li, Yong Liu, Weiping Wang
Optimal Convergence Rates for Distributed Nystroem Approximation. J. Mach. Learn. Res. 24 (2023)
Jian Li, Yong Liu, Weiping Wang
Semi-supervised vector-valued learning: Improved bounds and algorithms. Pattern Recognit. 138 (2023)
Xunyu Zhu, Jian Li, Yong Liu, Weiping Wang
Improving Differentiable Architecture Search via self-distillation. Neural Networks 167 (2023)
Jian Li, Bojian Wei, Yong Liu, Weiping Wang
Non-IID Distributed Learning with Optimal Mixture Weights. ECML/PKDD (4) (2022)
Yilin Kang, Yong Liu, Jian Li, Weiping Wang
Sharper Utility Bounds for Differentially Private Models. CoRR (2022)
Yilin Kang, Yong Liu, Jian Li, Weiping Wang
Sharper Utility Bounds for Differentially Private Models: Smooth and Non-smooth. CIKM (2022)
Yilin Kang, Yong Liu, Jian Li, Weiping Wang
Stability and Generalization of Differentially Private Minimax Problems. CoRR (2022)
Jian Li, Yong Liu, Weiping Wang
Convolutional spectral kernel learning with generalization guarantees. Artif. Intell. 313 (2022)
Bojian Wei, Jian Li, Yong Liu, Weiping Wang
Federated Learning for Non-IID Data: From Theory to Algorithm. PRICAI (1) (2021)
Jian Li, Yong Liu, Weiping Wang
Convolutional Spectral Kernel Learning. CoRR (2020)
Jian Li, Yong Liu, Weiping Wang
Automated Spectral Kernel Learning. AAAI (2020)
Jian Li, Yong Liu, Weiping Wang
Automated Spectral Kernel Learning. CoRR (2019)
Jian Li, Yong Liu, Rong Yin, Weiping Wang
Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis. IJCAI (2019)
Jian Li, Yong Liu, Rong Yin, Weiping Wang
Multi-Class Learning using Unlabeled Samples: Theory and Algorithm. IJCAI (2019)
Jian Li, Yong Liu, Weiping Wang
Distributed Learning with Random Features. CoRR (2019)
Jian Li, Yong Liu, Weiping Wang
Learning Vector-valued Functions with Local Rademacher Complexity. CoRR (2019)
Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang
Efficient Cross-Validation for Semi-Supervised Learning. CoRR (2019)
Yong Liu, Jian Li, Weiping Wang
Max-Diversity Distributed Learning: Theory and Algorithms. CoRR (2018)
Jian Li, Yong Liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang
Multi-Class Learning: From Theory to Algorithm. NeurIPS (2018)
Jian Li, Yong Liu, Hailun Lin, Yinliang Yue, Weiping Wang
Efficient Kernel Selection via Spectral Analysis. IJCAI (2017)