Bogdan Kulynych

Orcid: 0000-0001-5923-3931

According to our database1, Bogdan Kulynych authored at least 22 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Attack-Aware Noise Calibration for Differential Privacy.
CoRR, 2024

Accelerating Clinical Text Annotation in Underrepresented Languages: A Case Study on Text De-Identification.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

Evaluating Synthetic Data Augmentation to Correct for Data Imbalance in Realistic Clinical Prediction Settings.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

Tunable Privacy Risk Evaluation of Generative Adversarial Networks.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

The Fundamental Limits of Least-Privilege Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Prediction without Preclusion: Recourse Verification with Reachable Sets.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Adversarial Robustness for Tabular Data through Cost and Utility Awareness.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

Arbitrary Decisions Are a Hidden Cost of Differentially Private Training.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

2022
Disparate Vulnerability to Membership Inference Attacks.
Proc. Priv. Enhancing Technol., 2022

What You See is What You Get: Distributional Generalization for Algorithm Design in Deep Learning.
CoRR, 2022

What You See is What You Get: Principled Deep Learning via Distributional Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Epidose: A privacy-preserving epidemic dosimeter based on contact tracing.
Dataset, May, 2021

Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks.
CoRR, 2021

Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision.
CoRR, 2021

2020
POTs: protective optimization technologies.
Proceedings of the FAT* '20: Conference on Fairness, 2020

2019
Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning.
CoRR, 2019

zksk: A Library for Composable Zero-Knowledge Proofs.
Proceedings of the 18th ACM Workshop on Privacy in the Electronic Society, 2019

2018
Questioning the assumptions behind fairness solutions.
CoRR, 2018

Evading classifiers in discrete domains with provable optimality guarantees.
CoRR, 2018

ClaimChain: Improving the Security and Privacy of In-band Key Distribution for Messaging.
Proceedings of the 2018 Workshop on Privacy in the Electronic Society, 2018

2017
Feature importance scores and lossless feature pruning using Banzhaf power indices.
CoRR, 2017

ClaimChain: Decentralized Public Key Infrastructure.
CoRR, 2017


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