Ke Wang
Hivatkozott rá
Hivatkozott rá
Benign overfitting in multiclass classification: All roads lead to interpolation
K Wang, V Muthukumar, C Thrampoulidis
Advances in Neural Information Processing Systems 34, 24164-24179, 2021
Benign overfitting in binary classification of gaussian mixtures
K Wang, C Thrampoulidis
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization
K Wang, C Thrampoulidis
SIAM Journal on Mathematics of Data Science 4 (1), 260-284, 2022
On how to avoid exacerbating spurious correlations when models are overparameterized
T Behnia, K Wang, C Thrampoulidis
2022 IEEE International Symposium on Information Theory (ISIT), 121-126, 2022
Learning Gaussian graphical models with latent confounders
K Wang, A Franks, SY Oh
Journal of Multivariate Analysis 198, 105213, 2023
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
K Wang, V Muthukumar, C Thrampoulidis
IEEE Transactions on Information Theory 69 (12), 7909 - 7952, 2023
Computing SHAP Efficiently Using Model Structure Information
L Hu, K Wang
arXiv preprint arXiv:2309.02417, 2023
The Importance of Eigenstructure in High-dimensional Statistics: Examples from Overparameterized Machine Learning and Graphical Models
K Wang
University of California, Santa Barbara, 2022
Supplementary material for:“Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation”
K Wang, V Muthukumar, C Thrampoulidis
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Cikkek 1–9