Bogdan Kulynych
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POTs: Protective Optimization Technologies
B Kulynych, R Overdorf, C Troncoso, S Gürses
Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020
Disparate vulnerability: On the unfairness of privacy attacks against machine learning
M Yaghini, B Kulynych, G Cherubin, C Troncoso
arXiv preprint arXiv:1906.00389, 2019
ClaimChain: improving the security and privacy of in-band key distribution for messaging
B Kulynych, M Isaakidis, C Troncoso, G Danezis
Proceedings of the 2018 Workshop on Privacy in the Electronic Society, 86-103, 2018
Evading classifiers in discrete domains with provable optimality guarantees
B Kulynych, J Hayes, N Samarin, C Troncoso
arXiv preprint arXiv:1810.10939, 2018
Questioning the assumptions behind fairness solutions
R Overdorf, B Kulynych, E Balsa, C Troncoso, S Gürses
arXiv preprint arXiv:1811.11293, 2018
Feature importance scores and lossless feature pruning using Banzhaf power indices
B Kulynych, C Troncoso
NIPS 2017 Symposium on Interpretable Machine Learning, 2017
zksk: A Library for Composable Zero-Knowledge Proofs
W Lueks, B Kulynych, J Fasquelle, S Le Bail-Collet, C Troncoso
Proceedings of the 18th ACM Workshop on Privacy in the Electronic Society, 50-54, 2019
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks
K Albert, M Delano, B Kulynych, RSS Kumar
arXiv preprint arXiv:2107.10302, 2021
Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision
A Balayn, B Kulynych, S Guerses
arXiv preprint arXiv:2107.01824, 2021
POTs: Protective Optimization Technologies
S Gürses, B Kulynych, R Overdorf, C Troncoso
ACM Conference on Fairness, Accountability and Transparency, 2020
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