On the Saturation Effect of Kernel Ridge Regression. - Yicheng Li; Haobo Zhang 004; Qian Lin (ICLR, 2023)

On the Optimality of Misspecified Kernel Ridge Regression. - Haobo Zhang 004; Yicheng Li; Weihao Lu 002; Qian Lin (ICML, 2023)

On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay. - Yicheng Li; Haobo Zhang 004; Qian Lin (NeurIPS, 2023)

Kernel interpolation generalizes poorly. - Yicheng Li; Haobo Zhang 004; Qian Lin (CoRR, 2023)

Optimal Rate of Kernel Regression in Large Dimensions. - Weihao Lu 002; Haobo Zhang 004; Yicheng Li; Manyun Xu; Qian Lin (CoRR, 2023)

On the Saturation Effects of Spectral Algorithms in Large Dimensions. - Weihao Lu 002; Haobo Zhang 004; Yicheng Li; Qian Lin (NeurIPS, 2024)

Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions. - Haobo Zhang 004; Yicheng Li; Weihao Lu 002; Qian Lin (CoRR, 2024)

The phase diagram of kernel interpolation in large dimensions. - Haobo Zhang 004; Weihao Lu 002; Qian Lin (CoRR, 2024)

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories. - Haobo Zhang 004; Jianfa Lai; Yicheng Li; Qian Lin; Jun S. Liu (CoRR, 2024)

On the Optimality of Misspecified Spectral Algorithms. - Haobo Zhang 004; Yicheng Li; Qian Lin (J. Mach. Learn. Res., 2024)