Joseph P. Near
University of Vermont
H-index: 17
North America-United States
Top articles of Joseph P. Near
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
De-Identifying Government Datasets: Techniques and Governance | Simson Garfnkel Simson Garfinkel Joseph Near Aref Dajani Phyllis Singer | 2023/9/14 | |
Contextual linear types for differential privacy | ACM Transactions on Programming Languages and Systems | Matías Toro David Darais Chike Abuah Joseph P Near Damián Árquez | 2023/5/17 |
OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols | arXiv preprint arXiv:2302.10084 | Ivoline C Ngong Nicholas Gibson Joseph P Near | 2023/2/20 |
Programming Languages and Systems | ACM Transactions on | M Vukasovic A Prokopec A Boruch-Gruszecki M Odersky E Lee | 2023 |
Guidelines for Evaluating Differential Privacy Guarantees | Joseph Near David Darais Naomi Lefkovitz Gary Howarth | 2023/12/11 | |
Evaluating the Usability of Differential Privacy Tools with Data Practitioners | arXiv preprint arXiv:2309.13506 | Ivoline C Ngong Brad Stenger Joseph P Near Yuanyuan Feng | 2023/9/24 |
{PrivGuard}: Privacy regulation compliance made easier | Lun Wang Usmann Khan Joseph Near Qi Pang Jithendaraa Subramanian | 2022 | |
Improving Utility for Privacy-Preserving Analysis of Correlated Columns using Pufferfish Privacy | arXiv preprint arXiv:2209.10908 | Krystal Maughan Joseph P Near | 2022/9/22 |
Backpropagation clipping for deep learning with differential privacy | arXiv preprint arXiv:2202.05089 | Timothy Stevens Ivoline C Ngong David Darais Calvin Hirsch David Slater | 2022/2/10 |
Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers | arXiv preprint arXiv:2202.04504 | Krystal Maughan Ivoline C Ngong Joseph P Near | 2022/2/9 |
Secret Sharing Sharing For Highly Scalable Secure Aggregation | arXiv preprint arXiv:2201.00864 | Timothy Stevens Joseph Near Christian Skalka | 2022/1/3 |
Efficient differentially private secure aggregation for federated learning via hardness of learning with errors | Timothy Stevens Christian Skalka Christelle Vincent John Ring Samuel Clark | 2022 | |
Solo: a lightweight static analysis for differential privacy | Proceedings of the ACM on Programming Languages | Chike Abuah David Darais Joseph P Near | 2022/10/31 |
DDUO: General-purpose dynamic analysis for differential privacy | Chike Abuah Alex Silence David Darais Joseph P Near | 2021/6/21 | |
Programming Differential Privacy | Joseph P. Near Chike Abuah | 2021 | |
Zero knowledge static program analysis | Zhiyong Fang David Darais Joseph P Near Yupeng Zhang | 2021/11/12 | |
Methods for host-based intrusion detection with deep learning | Digital Threats: Research and Practice (DTRAP) | John H Ring IV Colin M Van Oort Samson Durst Vanessa White Joseph P Near | 2021/10/15 |
Do I get the privacy I need? Benchmarking utility in differential privacy libraries | arXiv preprint arXiv:2109.10789 | Gonzalo Munilla Garrido Joseph Near Aitsam Muhammad Warren He Roman Matzutt | 2021/9/22 |
Differential privacy for databases | Foundations and Trends® in Databases | Joseph P Near Xi He | 2021/7/21 |
Towards a measure of individual fairness for deep learning | arXiv preprint arXiv:2009.13650 | Krystal Maughan Joseph P Near | 2020/9/28 |
Co-Authors
