Solutions to Abel's Integral Equations in Distributions. - Chenkuan Li; Thomas Humphries; Hunter Plowman (Axioms, 2018)

Practical Over-Threshold Multi-Party Private Set Intersection. - Rasoul Akhavan Mahdavi; Thomas Humphries; Bailey Kacsmar; Simeon Krastnikov; Nils Lukas; John A. Premkumar; Masoumeh Shafieinejad; Simon Oya; Florian Kerschbaum; Erik-Oliver Blass (ACSAC, 2020)

Differentially Private Learning Does Not Bound Membership Inference. - Thomas Humphries; Matthew Rafuse; Lindsey Tulloch; Simon Oya; Ian Goldberg; Florian Kerschbaum (CoRR, 2020)

Self-Attention Generative Adversarial Network for Iterative Reconstruction of CT Images. - Ruiwen Xing; Thomas Humphries; Dong Si (CoRR, 2021)

An Extension of the iMOACO$ mathbb {_R}$ Algorithm Based on Layer-Set Selection. - Ashraf M. Abdelbar; Thomas Humphries; Jesús Guillermo Falcón-Cardona; Carlos A. Coello Coello (ANTS Conference, 2022)

Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics. - Thomas Humphries; Rasoul Akhavan Mahdavi; Shannon Veitch; Florian Kerschbaum (CCS, 2022)

Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration. - Miti Mazmudar; Thomas Humphries; Jiaxiang Liu; Matthew Rafuse; Xi He 001 (Proc. VLDB Endow., 2022)

Investigating Membership Inference Attacks under Data Dependencies. - Thomas Humphries; Simon Oya; Lindsey Tulloch; Matthew Rafuse; Ian Goldberg; Urs Hengartner; Florian Kerschbaum (CSF, 2023)

Gaggle: Genetic Algorithms on the GPU using PyTorch. - Lucas Fenaux; Thomas Humphries; Florian Kerschbaum (GECCO Companion, 2023)

Differentially Private Simple Genetic Algorithms. - Thomas Humphries; Florian Kerschbaum (Proc. Priv. Enhancing Technol., 2023)

Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. - Abdulrahman Diaa; Lucas Fenaux; Thomas Humphries; Marian Dietz; Faezeh Ebrahimianghazani; Bailey Kacsmar; Xinda Li 001; Nils Lukas; Rasoul Akhavan Mahdavi; Simon Oya; Ehsan Amjadian; Florian Kerschbaum (USENIX Security Symposium, 2024)

PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting. - Rasoul Akhavan Mahdavi; Nils Lukas; Faezeh Ebrahimianghazani; Thomas Humphries; Bailey Kacsmar; John A. Premkumar; Xinda Li 001; Simon Oya; Ehsan Amjadian; Florian Kerschbaum (USENIX Security Symposium, 2024)

FastLloyd: Federated, Accurate, Secure, and Tunable k-Means Clustering with Differential Privacy. - Abdulrahman Diaa; Thomas Humphries; Florian Kerschbaum (CoRR, 2024)