3 papers
stat.ML2026
Fixed-Gaussian Spectral Algorithms: Minimax Optimal Rates for Misspecified Learning and Transfer
Haotian Lin, Matthew Reimherr
The principal objective of this work is twofold within nonparametric regression settings: (1) to establish the minimax optimal convergence rates for fixed-bandwidth Gaussian kernel…
stat.ML2026
Pure Differential Privacy for Functional Summaries with a Laplace-like Process
Haotian Lin, Matthew Reimherr
Many existing mechanisms for achieving differential privacy (DP) on infinite-dimensional functional summaries typically involve embedding these functional summaries into finite-dim…
stat.ML2025
On Hypothesis Transfer Learning of Functional Linear Models
Haotian Lin, Matthew Reimherr
We study the transfer learning (TL) for the functional linear regression (FLR) under the Reproducing Kernel Hilbert Space (RKHS) framework, observing that the TL techniques in exis…