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stat.ML2025
On the Robustness of Kernel Ridge Regression Using the Cauchy Loss Function
Hongwei Wen, Annika Betken, Wouter Koolen
Robust regression aims to develop methods for estimating an unknown regression function in the presence of outliers, heavy-tailed distributions, or contaminated data, which can sev…
stat.ML2025
Median of Forests for Robust Density Estimation
Hongwei Wen, Annika Betken, Tao Huang
Robust density estimation refers to the consistent estimation of the density function even when the data is contaminated by outliers. We find that existing forest density estimatio…
stat.ML2023
Class Probability Matching Using Kernel Methods for Label Shift Adaptation
Hongwei Wen, Annika Betken, Hanyuan Hang
In domain adaptation, covariate shift and label shift problems are two distinct and complementary tasks. In covariate shift adaptation where the differences in data distribution ar…