1 citations · 2 across the 9 of their papers we have counts for
4 papers · 1 filter
The Zero Pattern of a Design Matrix Drives Multiple Descent in Over-parameterized Regression
Kevin Han Huang, Haoyu Ye, Somak Laha +1
Over-parameterized linear regression has been widely studied over the last decade. However, most existing works assume that the covariates are independent and that their covariance…
Universality of High-Dimensional Logistic Regression and a Novel CGMT under Dependence with Applications to Data Augmentation
Matthew Esmaili Mallory, Kevin Han Huang, Morgane Austern
Over the last decade, a wave of research has characterized the exact asymptotic risk of many high-dimensional models in the proportional regime. Two foundational results have drive…
Slow rates of approximation of U-statistics and V-statistics by quadratic forms of Gaussians
Kevin Han Huang, Peter Orbanz
We construct examples of degree-two U- and V-statistics of i.i.d.~heavy-tailed random vectors in , whose -th moments exist for , and provide tight…
A High-dimensional Convergence Theorem for U-statistics with Applications to Kernel-based Testing
Kevin H. Huang, Xing Liu, Andrew B. Duncan +1
We prove a convergence theorem for U-statistics of degree two, where the data dimension is allowed to scale with sample size . We find that the limiting distribution of a U-…