1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2025
Certified Data Removal Under High-dimensional Settings
Haolin Zou, Arnab Auddy, Yongchan Kwon +2
Machine unlearning focuses on the computationally efficient removal of specific training data from trained models, ensuring that the influence of forgotten data is effectively elim…
math.ST2024
Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
Haolin Zou, Arnab Auddy, Kamiar Rahnama Rad +1
Despite a large and significant body of recent work focused on estimating the out-of-sample risk of regularized models in the high dimensional regime, a theoretical understanding o…
math.ST2023★ 1 cited
Approximate Leave-one-out Cross Validation for Regression with Regularizers (extended version)
Arnab Auddy, Haolin Zou, Kamiar Rahnama Rad +1
The out-of-sample error (OO) is the main quantity of interest in risk estimation and model selection. Leave-one-out cross validation (LO) offers a (nearly) distribution-free yet co…