transport: Computation of optimal transport plans and Wasserstein distances D Schuhmacher, B Bähre, C Gottschlich, V Hartmann, F Heinemann, ...
R package version 0.12–2, 2020
50 2020 Semi-discrete optimal transport: a solution procedure for the unsquared Euclidean distance case V Hartmann, D Schuhmacher
Mathematical Methods of Operations Research 92 (1), 133-163, 2020
23 2020 Privacy-preserving classification with secret vector machines V Hartmann, K Modi, JM Pujol, R West
Proceedings of the 29th ACM International Conference on Information …, 2020
21 2020 transport: Computation of Optimal Transport Plans and Wasserstein Distances, r package version 0.11-1 D Schuhmacher, B Bähre, C Gottschlich, V Hartmann, F Heinemann, ...
14 2019 Distribution inference risks: Identifying and mitigating sources of leakage V Hartmann, L Meynent, M Peyrard, D Dimitriadis, S Tople, R West
2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 136-149, 2023
12 2023 Privacy-preserving distributed learning with secret gradient descent V Hartmann, R West
arXiv preprint arXiv:1906.11993, 2019
11 2019 Semi-discrete optimal transport-the case p= 1 V Hartmann, D Schuhmacher
arXiv preprint arXiv:1706.07650, 2017
10 2017 SoK: Memorization in General-Purpose Large Language Models V Hartmann, A Suri, V Bindschaedler, D Evans, S Tople, R West
arXiv preprint arXiv:2310.18362, 2023
8 2023 Package ‘transport’ D Schuhmacher, B Bähre, N Bonneel, C Gottschlich, V Hartmann, ...
R package version 1 (4), 2024
6 2024 A geometry-based approach for solving the transportation problem with Euclidean cost V Hartmann
arXiv preprint arXiv:1706.07403, 2017
3 2017 Language Model Decoding as Likelihood-Utility Alignment M Josifoski, M Peyrard, F Rajic, J Wei, D Paul, V Hartmann, B Patra, ...
arXiv preprint arXiv:2210.07228, 2022
2 2022 DiPPS: Differentially Private Propensity Scores for Bias Correction L Chen, V Hartmann, R West
Proceedings of the International AAAI Conference on Web and Social Media 17 …, 2023
1 2023 Privacy accounting conomics: Improving differential privacy composition via a posteriori bounds V Hartmann, V Bindschaedler, A Bentkamp, R West
arXiv preprint arXiv:2205.03470, 2022
1 2022 Neural Redshift: Random Networks are not Random Functions D Teney, A Nicolicioiu, V Hartmann, E Abbasnejad
arXiv preprint arXiv:2403.02241, 2024
2024 On the Choice of Databases in Differential Privacy Composition V Hartmann, V Bindschaedler, R West
arXiv preprint arXiv:2209.13697, 2022
2022 Secure Summation via Subset Sums: A New Primitive for Privacy-Preserving Distributed Machine Learning V Hartmann, R West
arXiv preprint arXiv:1906.11993, 2019
2019