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Dealer: An End-to-End Model Marketplace with Differential Privacy

Summary: Dealer presents the first end-to-end differentially private marketplace for ML models, pricing owners and buyers using Shapley value/coverage plus privacy and noise sensitivity. Dynamic programs optimize arbitrage-free pricing and budgeted training for maximum Shapley coverage. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hbed0c54033f2c497
Venue
VLDB
Year
2021
Pagerank
7.0249464e-05
Overall Rank
3,780 | 74.59%
DOI
10.14778/3447689.3447700

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{liu_vldb21,
        title = {{Dealer: An End-to-End Model Marketplace with Differential Privacy}},
        author = {Liu, Jinfei and Lou, Jian and Liu, Junxu and Xiong, Li and Pei, Jian and Sun, Jimeng},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {6},
        pages = {957--969},
        doi = {10.14778/3447689.3447700},
        url = {https://doi.org/10.14778/3447689.3447700},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 20 of 20 citing papers.

Rank Citing Paper Year Venue Pagerank
3,684 Secure Shapley Value for Cross-Silo Federated Learning 2023 VLDB 7.0989896e-05
3,729 Protecting Data Markets from Strategic Buyers 2022 SIGMOD 7.069419e-05
4,905 Data-Sharing Markets: Model, Protocol, and Algorithms to Incentivize the Formation of Data-Sharing Consortia 2023 SIGMOD 6.3624391e-05
4,928 Efficient Sampling Approaches to Shapley Value Approximation 2023 SIGMOD 6.3502007e-05
6,115 Equitable Data Valuation Meets the Right to Be Forgotten in Model Markets 2023 VLDB 5.8817545e-05
6,390 On Shapley Value in Data Assemblage Under Independent Utility 2022 VLDB 5.8010007e-05
7,242 Data and AI Model Markets: Opportunities for Data and Model Sharing, Discovery, and Integration 2023 VLDB 5.5773854e-05
8,150 P-Shapley: Shapley Values on Probabilistic Classifiers 2024 VLDB 5.39006e-05
8,305 Demonstration of Dealer: An End-to-End Model Marketplace with Differential Privacy 2021 VLDB 5.3587625e-05
9,071 Privacy and Accuracy-Aware AI/ML Model Deduplication 2025 SIGMOD 5.2283159e-05
9,723 Shapley Value Estimation Based on Differential Matrix 2025 SIGMOD 5.1349531e-05
10,414 ASSS: Adaptive Stratified Sampling for Shapley-like Values 2026 SIGMOD 4.9793485e-05
10,593 Reliable and Private Utility Signaling for Data Markets 2026 SIGMOD 4.9793485e-05
10,824 CaSh: Shapley Value Computation with Cache Optimization 2026 VLDB 4.9793485e-05
10,865 Local Shapley: Model-Induced Locality and Optimal Reuse in Data Valuation 2026 VLDB 4.9793485e-05
11,202 Computing Inconsistency Measures Under Differential Privacy 2025 SIGMOD 4.9793485e-05
11,354 Privacy-Enhanced Database Synthesis for Benchmark Publishing 2025 VLDB 4.9793485e-05
11,534 A Profit-Maximizing Data Marketplace with Differentially Private Federated Learning under Price Competition 2024 SIGMOD 4.9793485e-05
11,552 Performance-Based Pricing for Federated Learning via Auction 2024 VLDB 4.9793485e-05
11,643 DataPrice: An Interactive System for Pricing Datasets in Data Marketplaces 2024 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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