Matthew Reimherr

Shape And Structure Preserving Differential Privacy

Sep 21, 2022
Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra Slavkovic

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* 15 pages (including supplementary material and references), 3 figures (including supplementary material), to be published in NeurIPS 2022

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On Transfer Learning in Functional Linear Regression

Jun 09, 2022
Haotian Lin, Matthew Reimherr

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* 31 pages

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Differential Privacy Over Riemannian Manifolds

Nov 03, 2021
Matthew Reimherr, Karthik Bharath, Carlos Soto

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* 15 pages (including supplementary material and references), 2 figures (including supplementary material), published in NeurIPS

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Modern Non-Linear Function-on-Function Regression

Jul 29, 2021
Aniruddha Rajendra Rao, Matthew Reimherr

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* 6 figures, 5 tables (including supplementary material), 16 pages (including supplementary material). arXiv admin note: text overlap with arXiv:2104.09371

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Non-linear Functional Modeling using Neural Networks

Apr 19, 2021
Aniruddha Rajendra Rao, Matthew Reimherr

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* 3 figures, 8 tables (including supplementary material), 13 pages (including supplementary material)

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Modern Multiple Imputation with Functional Data

Nov 25, 2020
Aniruddha Rajendra Rao, Matthew Reimherr

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* 7 figures (including supplementary material), 8 tables (including supplementary material), 14 pages (including supplementary material)

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An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net

Jun 06, 2020
Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte

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KNG: The K-Norm Gradient Mechanism

May 23, 2019
Matthew Reimherr, Jordan Awan

* 13 pages, 2 figures

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Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA

Jan 30, 2019
Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra Slavković

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* 13 pages, 5 images, 2 tables

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