Matthew Reimherr

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 27

Top Topics

Differential Privacy

Augmented Lagrangian Method

Top Venues

J. Multivar. Anal.

Publications

Haotian Lin, Matthew Reimherr
Smoothness Adaptive Hypothesis Transfer Learning. CoRR (2024)
Aniruddha Rajendra Rao, Matthew Reimherr
Modern non-linear function-on-function regression. Stat. Comput. 33 (6) (2023)
Aniruddha Rajendra Rao, Matthew Reimherr
Nonlinear Functional Modeling Using Neural Networks. J. Comput. Graph. Stat. 32 (4) (2023)
Haotian Lin, Matthew Reimherr
Differentially Private Functional Summaries via the Independent Component Laplace Process. CoRR (2023)
Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra B. Slavkovic
Shape And Structure Preserving Differential Privacy. NeurIPS (2022)
Jeremy Seeman, Matthew Reimherr, Aleksandra B. Slavkovic
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms. CoRR (2022)
Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra B. Slavkovic
Shape And Structure Preserving Differential Privacy. CoRR (2022)
Jeremy Seeman, Aleksandra B. Slavkovic, Matthew Reimherr
A Formal Privacy Framework for Partially Private Data. CoRR (2022)
Haotian Lin, Matthew Reimherr
On Transfer Learning in Functional Linear Regression. CoRR (2022)
Aniruddha Rajendra Rao, Matthew Reimherr
Non-linear Functional Modeling using Neural Networks. CoRR (2021)
Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression. NeurIPS (2021)
Ardalan Mirshani, Matthew Reimherr
Adaptive function-on-scalar regression with a smoothing elastic net. J. Multivar. Anal. 185 (2021)
Jeremy Seeman, Matthew Reimherr, Aleksandra B. Slavkovic
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms. NeurIPS (2021)
Aniruddha Rajendra Rao, Matthew Reimherr
Modern Non-Linear Function-on-Function Regression. CoRR (2021)
Matthew Reimherr, Karthik Bharath, Carlos Soto
Differential Privacy Over Riemannian Manifolds. NeurIPS (2021)
Aniruddha Rajendra Rao, Matthew Reimherr
Modern Multiple Imputation with Functional Data. CoRR (2020)
Jeremy Seeman, Aleksandra B. Slavkovic, Matthew Reimherr
Private Posterior Inference Consistent with Public Information: A Case Study in Small Area Estimation from Synthetic Census Data. PSD (2020)
Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net. CoRR (2020)
Marzia A. Cremona, Hongyan Xu, Kateryna D. Makova, Matthew Reimherr, Francesca Chiaromonte, Pedro Madrigal
Functional data analysis for computational biology. Bioinform. 35 (17) (2019)
Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra B. Slavkovic
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA. CoRR (2019)
Matthew Reimherr, Jordan Awan
Elliptical Perturbations for Differential Privacy. CoRR (2019)
Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra B. Slavkovic
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA. ICML (2019)
Matthew Reimherr, Jordan Awan
KNG: The K-Norm Gradient Mechanism. CoRR (2019)
Matthew Reimherr, Jordan Awan
Elliptical Perturbations for Differential Privacy. NeurIPS (2019)
Matthew Reimherr, Jordan Awan
KNG: The K-Norm Gradient Mechanism. NeurIPS (2019)
Ardalan Mirshani, Matthew Reimherr, Aleksandra B. Slavkovic
Formal Privacy for Functional Data with Gaussian Perturbations. ICML (2019)
Piotr Kokoszka, Matthew Reimherr, Nikolas Wölfing
A randomness test for functional panels. J. Multivar. Anal. 151 (2016)