Research map / Federated learning and privacy / Differential privacy
Private Set Union with Multiple Contributions
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Studies differentially private private set union where each user contributes a bag of up to k items, giving algorithms that always report a superset of the union for the multiple-contribution setting.
Problem
Differentially private set union when each user holds a bag of up to k items, where naively reporting items present in only a few bags can violate privacy.
Approach
Differentially private algorithms that always report a superset of the union of items, with the goal of minimizing the extra items reported while handling multiple contributions per user.
Closest papers by meaning
- Incorporating Item Frequency for Differentially Private Set Union (AAAI 2022 · similarity 0.90)
- Scalable Private Partition Selection via Adaptive Weighting (ICML 2025 · similarity 0.87)
- Faster Differentially Private Top-$k$ Selection: A Joint Exponential Mechanism with Pruning (NeurIPS 2024 · similarity 0.85)
- On the Price of Differential Privacy for Hierarchical Clustering (ICLR 2025 · similarity 0.84)
- Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model (ICML 2025 · similarity 0.84)
- Differentially Private Gomory-Hu Trees (NeurIPS 2025 · similarity 0.84)
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