Publications

2026

1. Risk Equivalence Between RKHS Regression and Sequence Models for Lipschitz Spectral Algorithms

   Yicheng Li, Yuqian Cheng, Zhuo Chen, and Qian Lin

   arXiv preprint, arXiv:2609.08817, Sep 2026

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2. Exact Asymptotic Efficiency under zCDP: Diameter-Constrained Information Geometry

   T. Tony Cai and Yicheng Li (alphabetical order)

   arXiv preprint, arXiv:2609.16895, Sep 2026

   PDF arXiv
3. Transfer Learning for Covariance Matrix Estimation: Optimality and Adaptivity

   T. Tony Cai, Dongwoo Kim, Yicheng Li, and Dongdong Xiang (alphabetical order)

   Journal of the American Statistical Association, Aug 2026

   DOI PDF URL
4. Exact Generalization Error Curves of Kernel Ridge Regression for Functional Moment Estimation

   Yinan Ding and Yicheng Li

   arXiv preprint, arXiv:2607.23666, Jul 2026

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5. The Cost of Discretization in Functional Linear Regression: Minimax Rates and Adaptation

   T. Tony Cai and Yicheng Li (alphabetical order)

   arXiv preprint, arXiv:2607.09350, Jul 2026

   PDF arXiv
6. Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories

   Haobo Zhang, Jianfa Lai, Yicheng Li, Qian Lin, and Jun S. Liu

   Statistical Learning and Data Science, Sep 2026

   arXiv:2412.18756v2

   DOI PDF URL
7. A Van Trees Lower Bound for Fully Interactive Differentially Private Federated Learning

   T. Tony Cai and Yicheng Li (alphabetical order)

   arXiv preprint, arXiv:2605.19813v2, Jul 2026

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8. Large Dimensional Kernel Ridge Regression: Extending to Product Kernels

   Yang Zhou, Yicheng Li, Yuqian Cheng, and Qian Lin

   arXiv preprint, arXiv:2605.14524, May 2026

   PDF arXiv
9. Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels

   Dongming Huang, Zhifan Li, Yicheng Li, and Qian Lin

   In Proceedings of the 43rd International Conference on Machine Learning, 2026

   Spotlight

   DOI PDF URL
10. Minimax and Adaptive Covariance Matrix Estimation under Differential Privacy

    T. Tony Cai and Yicheng Li (alphabetical order)

    arXiv preprint, arXiv:2603.19703, Mar 2026

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11. Generalization Error Curves for Analytic Spectral Algorithms under Power-Law Decay

    Yicheng Li, Weiye Gan, Zuoqiang Shi, and Qian Lin

    Applied and Computational Harmonic Analysis, Aug 2026

    DOI PDF URL

2025

1. Several Supporting Evidences for the Adaptive Feature Program

   Yicheng Li and Qian Lin

   arXiv preprint, arXiv:2511.09425, Nov 2025

   PDF arXiv
2. Differentially Private Functional Linear regression: Optimal Algorithms and Theoretical Guarantees

   Yicheng Li and T. Tony Cai

   Sep 2025
3. Functional Virtual Adversarial Training for Semi-Supervised Time Series Classification

   Qingyi Pan and Yicheng Li (Corresponding author)

   In 39th Conference on Neural Information Processing Systems (NeurIPS 2025), Sep 2025

   PDF OpenReview
4. Diagonal Over-Parameterization in Reproducing Kernel Hilbert Spaces as an Adaptive Feature Model: Generalization and Adaptivity

   Yicheng Li and Qian Lin

   arXiv preprint, arXiv:2501.08679, Jan 2025

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5. Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions

   Haobo Zhang, Yicheng Li, Weihao Lu, and Qian Lin

   Journal of Machine Learning Research, 2025

   PDF URL

2024

1. On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory

   Guhan Chen, Yicheng Li, and Qian Lin

   In 38th Conference on Neural Information Processing Systems (NeurIPS 2024), Sep 2024

   DOI PDF OpenReview
2. Improving Adaptivity via Over-Parameterization in Sequence Models

   Yicheng Li and Qian Lin

   In 38th Conference on Neural Information Processing Systems (NeurIPS 2024), Sep 2024

   DOI PDF OpenReview
3. On the Saturation Effects of Spectral Algorithms in Large Dimensions

   Weihao Lu, Haobo Zhang, Yicheng Li, and Qian Lin

   In 38th Conference on Neural Information Processing Systems (NeurIPS 2024), Sep 2024

   DOI PDF OpenReview
4. On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains

   Yicheng Li, Zixiong Yu, Guhan Chen, and Qian Lin

   Journal of Machine Learning Research, 2024

   PDF URL
5. Kernel Interpolation Generalizes Poorly

   Yicheng Li, Haobo Zhang, and Qian Lin

   Biometrika, 2024

   DOI PDF URL
6. On the Optimality of Misspecified Spectral Algorithms

   Haobo Zhang, Yicheng Li (Co-first author), and Qian Lin

   Journal of Machine Learning Research, 2024

   PDF URL

2023

1. Optimal Rate of Kernel Regression in Large Dimensions

   Weihao Lu, Haobo Zhang, Yicheng Li, Manyun Xu, and Qian Lin

   arXiv preprint, arXiv:2309.04268, Sep 2023

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2. On the Saturation Effect of Kernel Ridge Regression

   Yicheng Li, Haobo Zhang, and Qian Lin

   In 11th International Conference on Learning Representations (ICLR 2023), Feb 2023

   arXiv PDF OpenReview
3. On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-Law Decay

   Yicheng Li, Haobo Zhang, and Qian Lin

   In 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023

   PDF OpenReview
4. On the Optimality of Misspecified Kernel Ridge Regression

   Haobo Zhang, Yicheng Li, Weihao Lu, and Qian Lin

   In 40th International Conference on Machine Learning (ICML 2023), 2023

   PDF OpenReview