Federated Calibration and Evaluation of Binary Classifiers
Summary: Protocols for calibrating binary classifier scores and computing precision/recall/accuracy/ROC‑AUC in federated settings without centralizing labels, supporting secure aggregation, distributed DP, and local DP. Theorems and experiments quantify privacy–utility–data‑efficiency tradeoffs and provide practical criteria to decide when federated calibration/evaluation is viable. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Graham Cormode (Meta)
- 2. Igor L. Markov (Meta)
BibTeX Citation
@article{cormode_vldb23,
title = {{Federated Calibration and Evaluation of Binary Classifiers}},
author = {Cormode, Graham and Markov, Igor L.},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {11},
pages = {3253--3265},
doi = {10.14778/3611479.3611523},
url = {https://doi.org/10.14778/3611479.3611523},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,121 | Answering Range Queries Under Local Differential Privacy | 2019 | VLDB | 7.7357038e-05 |
| 4,132 | Answering Multi-Dimensional Range Queries under Local Differential Privacy | 2021 | VLDB | 6.8832571e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,869 | Federated Data Distribution Shift Estimation | 2025 | VLDB |
| 2 | 8,917 | A Blockchain System for Clustered Federated Learning with Peer-to-Peer Knowledge Transfer | 2024 | VLDB |
| 3 | 3,237 | BlindFL: Vertical Federated Machine Learning without Peeking into Your Data | 2022 | SIGMOD |
| 4 | 1,249 | Privacy Preserving Vertical Federated Learning for Tree-based Models | 2020 | VLDB |
| 5 | 6,366 | Practical Differentially Private and Byzantine-resilient Federated Learning | 2023 | SIGMOD |
| 6 | 7,833 | An Introduction to Federated Computation | 2022 | SIGMOD |
| 7 | 5,588 | Federated Matrix Factorization with Privacy Guarantee | 2022 | VLDB |
| 8 | 6,353 | Differentially Private Vertical Federated Clustering | 2023 | VLDB |
| 9 | 4,446 | Projected Federated Averaging with Heterogeneous Differential Privacy | 2022 | VLDB |
| 10 | 8,045 | Contributions Estimation in Federated Learning: A Comprehensive Experimental Evaluation | 2024 | VLDB |