4 citations · 5 across the 4 of their papers we have counts for
4 papers
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…
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
Many existing two-phase kernel-based hypothesis transfer learning algorithms employ the same kernel regularization across phases and rely on the known smoothness of functions to ob…
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…
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…