High Performance Logistic Regression for Privacy-Preserving Genome Analysis
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Abstract (arXiv)
In this paper, we present a secure logistic regression training protocol and its implementation, with a new subprotocol to securely compute the activation function. To the best of our knowledge, we present the fastest existing secure Multi-Party Computation implementation for training logistic regression models on high dimensional genome data distributed across a local area network.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Feb 2020.
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Citing papers per year: 2021: 4; 2022: 4; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
9 papers.
- 2021Privacy-Preserving Feature Selection with Secure Multiparty Computationcited by 12
- 2022Privacy-Preserving Logistic Regression Training with A Faster Gradient Variantcited by 7
- 2022Secure Multiparty Computation for Synthetic Data Generation from Distributed Datacited by 6
- 2021Privacy-Preserving Training of Tree Ensembles over Continuous Datacited by 5
- 2022PrivFair: a Library for Privacy-Preserving Fairness Auditingcited by 4
- 2021Fast Privacy-Preserving Text Classification based on Secure Multiparty Computationcited by 2
- 2022Training Differentially Private Models with Secure Multiparty Computationcited by 2
- 2026Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddingscited by 2
- 2021Round and Communication Balanced Protocols for Oblivious Evaluation of Finite State Machinescited by 0
- 2026Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddings3 Sep 2026
- 2022Secure Multiparty Computation for Synthetic Data Generation from Distributed Data13 Oct 2022
- 2022PrivFair: a Library for Privacy-Preserving Fairness Auditing8 Feb 2022
- 2022Training Differentially Private Models with Secure Multiparty Computation5 Feb 2022
- 2022Privacy-Preserving Logistic Regression Training with A Faster Gradient Variant26 Jan 2022
- 2021Privacy-Preserving Training of Tree Ensembles over Continuous Data5 Jun 2021
- 2021Round and Communication Balanced Protocols for Oblivious Evaluation of Finite State Machines20 Mar 2021
- 2021Privacy-Preserving Feature Selection with Secure Multiparty Computation6 Feb 2021
- 2021Fast Privacy-Preserving Text Classification based on Secure Multiparty Computation18 Jan 2021