Database Paper Browser

Back to papers

FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data

Summary: FEAST uses conditional mutual information for federated vertical feature selection on relational data, cutting redundancy. A compact, efficient protocol minimizes exchanged statistics to protect raw data, delivering strong accuracy at low cost. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6611
Venue
SIGMOD
Year
2023
Pagerank
4.351469e-05
Overall Rank
9,328 | 35.18%
DOI
10.1145/3588961

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
6,498 Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System 2023 VLDB 5.031352e-05
8,453 Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs 2024 VLDB 4.5022073e-05
10,694 PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning 2025 VLDB 4.1905499e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 17 of 17 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,099 Privacy Preserving Vertical Federated Learning for Tree-based Models 2020 VLDB 0.00014063542
1,899 VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning 2021 SIGMOD 0.00010171063
3,157 ARM-Net: Adaptive Relation Modeling Network for Structured Data 2021 SIGMOD 7.4679349e-05
3,475 BlindFL: Vertical Federated Machine Learning without Peeking into Your Data 2022 SIGMOD 7.0590045e-05
3,641 OceanBase: A 707 Million tpmC Distributed Relational Database System 2022 VLDB 6.8877808e-05
4,538 Privacy Preserving Schema and Data Matching 2007 SIGMOD 6.0987424e-05
4,614 F-IVM: Learning over Fast-Evolving Relational Data 2020 SIGMOD 6.042045e-05
4,745 Rafiki: Machine Learning as an Analytics Service System 2019 VLDB 5.9466323e-05
4,761 Automated Feature Engineering for Algorithmic Fairness 2021 VLDB 5.9341687e-05
4,806 Projected Federated Averaging with Heterogeneous Differential Privacy 2022 VLDB 5.9045984e-05
5,227 Enabling SQL-based Training Data Debugging for Federated Learning 2022 VLDB 5.6156523e-05
5,784 Federated Matrix Factorization with Privacy Guarantee 2022 VLDB 5.3259797e-05
5,959 Fine-grained Concept Linking using Neural Networks in Healthcare 2018 SIGMOD 5.2514585e-05
7,605 Causal Feature Selection for Algorithmic Fairness 2022 SIGMOD 4.6943015e-05
7,702 ExDRa: Exploratory Data Science on Federated Raw Data 2021 SIGMOD 4.6689015e-05
7,855 An Introduction to Federated Computation 2022 SIGMOD 4.6305904e-05
13,232 DyHealth: Making Neural Networks Dynamic for Effective Healthcare Analytics 2022 VLDB -
Previous Page 1 / 1 Next

Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
1,899 VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning 2021 SIGMOD 0.00010171063
10,723 Federated and Balanced Clustering for High-dimensional Data 2025 VLDB 4.1905499e-05
8,736 Historical Embedding-Guided Efficient Large-Scale Federated Graph Learning 2024 SIGMOD 4.4520434e-05
6,615 Differentially Private Vertical Federated Clustering 2023 VLDB 4.9882647e-05
3,475 BlindFL: Vertical Federated Machine Learning without Peeking into Your Data 2022 SIGMOD 7.0590045e-05
10,694 PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning 2025 VLDB 4.1905499e-05
13,165 Communication Efficient and Provable Federated Unlearning 2024 VLDB -
8,664 Contributions Estimation in Federated Learning: A Comprehensive Experimental Evaluation 2024 VLDB 4.4676883e-05
9,965 Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates 2022 VLDB 4.2229209e-05
11,212 FedCSS: Joint Client-and-Sample Selection for Hard Sample-Aware Noise-Robust Federated Learning 2023 SIGMOD 4.1905499e-05