"kernel ridge regression" Papers
11 papers found
Conference
A duality framework for analyzing random feature and two-layer neural networks
Hongrui Chen, Jihao Long, Lei Wu
NEURIPS 2025arXiv:2305.05642
2
citations
A Geometrical Analysis of Kernel Ridge Regression and its Applications
Georgios Gavrilopoulos, Guillaume Lecué, Zong Shang
NEURIPS 2025arXiv:2404.07709
2
citations
Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning
Dechen Zhang, Zhenmei Shi, Zhang et al.
NEURIPS 2025arXiv:2510.15363
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
Kaizheng Wang
NEURIPS 2025arXiv:2302.10160
15
citations
Ridge Boosting is Both Robust and Efficient
David Bruns-Smith, Zhongming Xie, Avi Feller
NEURIPS 2025spotlightarXiv:2510.22083
BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges
Hoyong Choi, Nohyun Ki, Hye Won Chung
ICML 2024arXiv:2406.03057
9
citations
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios et al.
ICML 2024arXiv:2402.01297
12
citations
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
Yihang Chen, Fanghui Liu, Taiji Suzuki et al.
ICML 2024arXiv:2406.03171
3
citations
Quasi-Monte Carlo Features for Kernel Approximation
ZHEN HUANG, Jiajin Sun, Yian Huang
ICML 2024spotlightarXiv:2503.06041
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
ICML 2024arXiv:2402.14966
11
citations
Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features
Chao Wang, Xin Bing, Xin HE et al.
ICML 2024spotlight