251 citations · 487 across the 35 of their papers we have counts for
6 papers · 1 filter
Fast and Fair Simultaneous Confidence Bands for Functional Parameters
Dominik Liebl, Matthew Reimherr
Quantifying uncertainty using confidence regions is a central goal of statistical inference. Despite this, methodologies for confidence bands in Functional Data Analysis are still…
Adaptive Function-on-Scalar Regression with a Smoothing Elastic Net
Ardalan Mirshani, Matthew Reimherr
This paper presents a new methodology, called AFSSEN, to simultaneously select significant predictors and produce smooth estimates in a high-dimensional function-on-scalar linear m…
KNG: The K-Norm Gradient Mechanism
Matthew Reimherr, Jordan Awan
This paper presents a new mechanism for producing sanitized statistical summaries that achieve \emph{differential privacy}, called the \emph{K-Norm Gradient} Mechanism, or KNG. Thi…
Elliptical Perturbations for Differential Privacy
Matthew Reimherr, Jordan Awan
We study elliptical distributions in locally convex vector spaces, and determine conditions when they can or cannot be used to satisfy differential privacy (DP). A requisite condit…
Optimal Function-on-Scalar Regression over Complex Domains
Matthew Reimherr, Bharath Sriperumbudur, Hyun Bin Kang
In this work we consider the problem of estimating function-on-scalar regression models when the functions are observed over multi-dimensional or manifold domains and with potentia…
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA
Jordan Awan, Ana Kenney, Matthew Reimherr +1
The exponential mechanism is a fundamental tool of Differential Privacy (DP) due to its strong privacy guarantees and flexibility. We study its extension to settings with summaries…