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Bogdan Kulynych
Bogdan Kulynych
Postdoc at Lausanne University Hospital
Bestätigte E-Mail-Adresse bei chuv.ch - Startseite
Titel
Zitiert von
Zitiert von
Jahr
POTs: Protective Optimization Technologies
B Kulynych, R Overdorf, C Troncoso, S Gürses
Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020
106*2020
Disparate Vulnerability to Membership Inference Attacks
B Kulynych, M Yaghini, G Cherubin, M Veale, C Troncoso
Proceedings on Privacy Enhancing Technologies, 460–480, 2022
91*2022
Participatory approaches to machine learning
B Kulynych, D Madras, S Milli, ID Raji, A Zhou, R Zemel
International Conference on Machine Learning Workshop 7, 2020
442020
Evading classifiers in discrete domains with provable optimality guarantees
B Kulynych, J Hayes, N Samarin, C Troncoso
arXiv preprint arXiv:1810.10939, 2018
292018
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
29*2018
Questioning the assumptions behind fairness solutions
R Overdorf, B Kulynych, E Balsa, C Troncoso, S Gürses
NeurIPS 2018 “Critiquing and Correcting Trends in Machine Learning” Workshop, 2018
232018
Adversarial Robustness for Tabular Data through Cost and Utility Awareness
K Kireev, B Kulynych, C Troncoso
NDSS, 2023
212023
Arbitrary Decisions are a Hidden Cost of Differentially Private Training
B Kulynych, H Hsu, C Troncoso, FP Calmon
FAccT, 2023
202023
What You See is What You Get: Principled Deep Learning via Distributional Generalization
B Kulynych, YY Yang, Y Yu, J Błasiok, P Nakkiran
NeurIPS, 2022
20*2022
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks
K Albert, M Delano, B Kulynych, RSS Kumar
ICML 2021 “A Blessing in Disguise: The Prospects and Perils of Adversarial …, 2021
72021
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
72019
Prediction without Preclusion: Recourse Verification with Reachable Sets
A Kothari, B Kulynych, TW Weng, B Ustun
ICLR, 2024
62024
Attack-Aware Noise Calibration for Differential Privacy
B Kulynych, JF Gomez, G Kaissis, FP Calmon, C Troncoso
NeurIPS, 2024
42024
Causal prediction can induce performative stability
B Kulynych
ICML 2022: Workshop on Spurious Correlations, Invariance and Stability, 2022
42022
Exploring Data Pipelines through the Process Lens: a Reference Model for Computer Vision
A Balayn, B Kulynych, S Guerses
CVPR 2021 “Beyond Fair Computer Vision” Workshop, 2021
42021
A Scoping Review of Privacy and Utility Metrics in Medical Synthetic Data
JLR Bayrem Kaabachi, Jérémie Despraz, Thierry Meurers, Karen Otte, Mehmed ...
npj Digital Medicine 8 (50), 2025
22025
Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts
G Starke, F Gille, A Termine, YSJ Aquino, R Chavarriaga, A Ferrario, ...
Journal of medical Internet research 27, e56306, 2025
12025
Tunable Privacy Risk Evaluation of Generative Adversarial Networks
B Kaabachi, F Briki, B Kulynych, J Despraz, JL Raisaro
Digital Health and Informatics Innovations for Sustainable Health Care …, 2024
12024
Evaluating Synthetic Data Augmentation to Correct for Data Imbalance in Realistic Clinical Prediction Settings
N Wahler, B Kaabachi, B Kulynych, J Despraz, C Simon, JL Raisaro
Digital Health and Informatics Innovations for Sustainable Health Care …, 2024
12024
The Fundamental Limits of Least-Privilege Learning
T Stadler, B Kulynych, N Papernot, M Gastpar, C Troncoso
ICML, 2024
12024
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