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Thomas Humphries
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2020 – today
- 2024
- [c7]Abdulrahman Diaa, Lucas Fenaux, Thomas Humphries, Marian Dietz, Faezeh Ebrahimianghazani, Bailey Kacsmar, Xinda Li, Nils Lukas, Rasoul Akhavan Mahdavi, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. USENIX Security Symposium 2024 - [c6]Rasoul Akhavan Mahdavi, Nils Lukas, Faezeh Ebrahimianghazani, Thomas Humphries, Bailey Kacsmar, John A. Premkumar, Xinda Li, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting. USENIX Security Symposium 2024 - [i7]Abdulrahman Diaa, Thomas Humphries, Florian Kerschbaum:
FastLloyd: Federated, Accurate, Secure, and Tunable k-Means Clustering with Differential Privacy. CoRR abs/2405.02437 (2024) - 2023
- [j3]Thomas Humphries, Florian Kerschbaum:
Differentially Private Simple Genetic Algorithms. Proc. Priv. Enhancing Technol. 2023(4): 540-558 (2023) - [c5]Thomas Humphries, Simon Oya, Lindsey Tulloch, Matthew Rafuse, Ian Goldberg, Urs Hengartner, Florian Kerschbaum:
Investigating Membership Inference Attacks under Data Dependencies. CSF 2023: 473-488 - [c4]Lucas Fenaux
, Thomas Humphries
Gaggle: Genetic Algorithms on the GPU using PyTorch. GECCO Companion 2023: 2358-2361 - [i6]Abdulrahman Diaa, Lucas Fenaux, Thomas Humphries, Marian Dietz, Faezeh Ebrahimianghazani, Bailey Kacsmar, Xinda Li, Nils Lukas, Rasoul Akhavan Mahdavi, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. CoRR abs/2306.08538 (2023) - [i5]Rasoul Akhavan Mahdavi, Nils Lukas, Faezeh Ebrahimianghazani, Thomas Humphries, Bailey Kacsmar, John A. Premkumar, Xinda Li, Simon Oya, Ehsan Amjadian, Florian Kerschbaum:
PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting. CoRR abs/2310.14565 (2023) - 2022
- [j2]Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He:
Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration. Proc. VLDB Endow. 16(4): 574-586 (2022) - [c3]Ashraf M. Abdelbar
An Extension of the iMOACO$\mathbb {_R}$ Algorithm Based on Layer-Set Selection. ANTS Conference 2022: 266-274 - [c2]Thomas Humphries, Rasoul Akhavan Mahdavi, Shannon Veitch, Florian Kerschbaum:
Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics. CCS 2022: 1459-1472 - [i4]Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He:
Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration. CoRR abs/2211.15732 (2022) - 2021
- [i3]Thomas Humphries, Rasoul Akhavan Mahdavi, Shannon Veitch, Florian Kerschbaum:
Selective MPC: Distributed Computation of Differentially Private Key Value Statistics. CoRR abs/2107.12407 (2021) - [i2]Ruiwen Xing, Thomas Humphries, Dong Si:
Self-Attention Generative Adversarial Network for Iterative Reconstruction of CT Images. CoRR abs/2112.12810 (2021) - 2020
- [c1]Rasoul Akhavan Mahdavi, Thomas Humphries, Bailey Kacsmar, Simeon Krastnikov, Nils Lukas, John A. Premkumar, Masoumeh Shafieinejad, Simon Oya, Florian Kerschbaum, Erik-Oliver Blass:
Practical Over-Threshold Multi-Party Private Set Intersection. ACSAC 2020: 772-783 - [i1]Thomas Humphries, Matthew Rafuse, Lindsey Tulloch, Simon Oya, Ian Goldberg, Florian Kerschbaum:
Differentially Private Learning Does Not Bound Membership Inference. CoRR abs/2010.12112 (2020)
2010 – 2019
- 2018
- [j1]Chenkuan Li
Solutions to Abel's Integral Equations in Distributions. Axioms 7(3): 66 (2018)
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