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Phillipp Schoppmann
Phillipp Schoppmann
Research Scientist, Google
Verified email at google.com
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Cited by
Cited by
Year
Privacy-Preserving Distributed Linear Regression on High-Dimensional Data
A Gascón, P Schoppmann, B Balle, M Raykova, J Doerner, S Zahur, ...
Proceedings on Privacy Enhancing Technologies 2017 (4), 345–364, 2017
2462017
Secure Linear Regression on Vertically Partitioned Datasets.
A Gascón, P Schoppmann, B Balle, M Raykova, J Doerner, S Zahur, ...
IACR Cryptology ePrint Archive 2016 (892), 2016
1102016
VOLE-PSI: Fast OPRF and Circuit-PSI from Vector-OLE
P Rindal, P Schoppmann
Annual International Conference on the Theory and Applications of …, 2021
872021
Communication–Computation Trade-offs in PIR
A Ali, T Lepoint, S Patel, M Raykova, P Schoppmann, K Seth, K Yeo
30th USENIX Security Symposium (USENIX Security 21), 1811–1828, 2021
722021
Distributed Vector-OLE: Improved Constructions and Implementation
P Schoppmann, A Gascón, L Reichert, M Raykova
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019
702019
A general purpose transpiler for fully homomorphic encryption
S Gorantala, R Springer, S Purser-Haskell, W Lam, R Wilson, A Ali, ...
arXiv preprint arXiv:2106.07893, 2021
382021
Make Some ROOM for the Zeros: Data Sparsity in Secure Distributed Machine Learning
P Schoppmann, A Gascón, M Raykova, B Pinkas
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019
252019
Mainzelliste SecureEpiLinker (MainSEL): Privacy-Preserving Record Linkage using Secure Multi-Party Computation
S Stammler, T Kussel, P Schoppmann, F Stampe, G Tremper, ...
Bioinformatics 38 (6), 1657–1668, 2022
232022
Asymmetric private set intersection with applications to contact tracing and private vertical federated machine learning
N Angelou, A Benaissa, B Cebere, W Clark, AJ Hall, MA Hoeh, D Liu, ...
arXiv preprint arXiv:2011.09350, 2020
232020
Distributed, private, sparse histograms in the two-server model
J Bell, A Gascon, B Ghazi, R Kumar, P Manurangsi, M Raykova, ...
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022
172022
Private Nearest Neighbors Classification in Federated Databases
P Schoppmann, A Gascón, B Balle
IACR Cryptology ePrint Archive 2018 (289), 2018
132018
Secure and Scalable Document Similarity on Distributed Databases: Differential Privacy to the Rescue
P Schoppmann, L Vogelsang, A Gascón, B Balle
Proceedings on Privacy Enhancing Technologies 2020 (2), 209–229, 2020
112020
Verifiable Distributed Aggregation Functions
H Davis, C Patton, M Rosulek, P Schoppmann
Proceedings on Privacy-Enhancing Technologies 2023 (4), 578–592, 2023
82023
A Secure Multi-Party Computation Protocol for Time-To-Event Analyses
L Vogelsang, M Lehne, P Schoppmann, F Prasser, S Thun, ...
Medical Informatics Europe 2020: Digital Personalized Health and Medicine, 8–12, 2020
72020
Communication-Efficient Secure Logistic Regression
A Agarwal, S Peceny, M Raykova, P Schoppmann, K Seth
Cryptology ePrint Archive, 2022
42022
PPML'19: Privacy Preserving Machine Learning
B Balle, A Gascón, O Ohrimenko, M Raykova, P Schoppmann, ...
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019
22019
Poster: Solving Private Systems of Linear Equations with Garbled Circuits
P Schoppmann, A Gascón, B Balle
IEEE Symposium on Security and Privacy, 2016
12016
Distributed, Private, Sparse Histograms in the Two-Server Model
B Ghazi, S Ravikumar, P Manurangsi, MP Raykova, A Gascon, JH Bell, ...
US Patent App. 18/297,084, 2023
2023
Secure Computation Protocols for Privacy-Preserving Machine Learning
P Schoppmann
Humboldt-Universität zu Berlin, 2021
2021
Outsourcing exponentiation in a private group
K Yeo, S Patel, P Schoppmann
US Patent 11,005,654, 2021
2021
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