251 citations · 487 across the 35 of their papers we have counts for
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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…
Shape And Structure Preserving Differential Privacy
Carlos Soto, Karthik Bharath, Matthew Reimherr +1
It is common for data structures such as images and shapes of 2D objects to be represented as points on a manifold. The utility of a mechanism to produce sanitized differentially p…
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…
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net
Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte
Feature selection is an important and active research area in statistics and machine learning. The Elastic Net is often used to perform selection when the features present non-negl…