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Matthew Regehr

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

Matthew T. Regehr

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affiliation: University of Waterloo, Cheriton School of Computer Science, Waterloo, ON, Canada
affiliation (former): University of Alberta, Department of Computing Science, Edmonton, AB, Canada

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2026
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Matthew Regehr, Bingshan Hu, Ethan Leeman, Pasin Manurangsi, Pierre Tholoniat, Mathias Lécuyer:
Natural Privacy Filters Are Not Always Free: A Characterization of Free Natural Filters. CoRR abs/2602.15815 (2026)
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Matthew Regehr, Gautam Kamath, Andrew Lowy:
Near-Optimal Pure Machine Unlearning for Smooth Strongly Convex Losses. CoRR abs/2606.01527 (2026)
2025
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Gautam Kamath, Alireza F. Pour, Matthew Regehr, David P. Woodruff:
Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph. NeurIPS 2025
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Christian Janos Lebeda, Matthew Regehr, Gautam Kamath, Thomas Steinke:
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms Under Composition. SaTML 2025: 996-1006
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  - journals/corr/abs-2509-16180
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Gautam Kamath, Alireza F. Pour, Matthew Regehr, David P. Woodruff:
Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph. CoRR abs/2509.16180 (2025)
2024
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Christian Janos Lebeda, Matthew Regehr, Gautam Kamath, Thomas Steinke:
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition. CoRR abs/2405.20769 (2024)
2023
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Gautam Kamath, Argyris Mouzakis, Matthew Regehr, Vikrant Singhal, Thomas Steinke, Jonathan R. Ullman:
A Bias-Variance-Privacy Trilemma for Statistical Estimation. CoRR abs/2301.13334 (2023)
2021
[i1]
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Matthew T. Regehr, Alex Ayoub:
An Elementary Proof that Q-learning Converges Almost Surely. CoRR abs/2108.02827 (2021)
2020
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Matthew Regehr, Andrew Volk, Michelle Noga, Kumaradevan Punithakumar:
Machine Learning and Graph Based Approach to Automatic Right Atrial Segmentation from Magnetic Resonance Imaging. ISBI 2020: 826-829

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Schloss Dagstuhl - Leibniz Center for Informatics is a member of the Leibniz Association and is funded by the federal government of Germany and the states of Germany, especially Saarland and Rhineland‑Palatinate.