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Privacy-Preserving Analysis of Distributed Biomedical Data: Designing Efficient and Secure Multiparty Computations Using Distributed Statistical Learning Theory
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-68535-9_40openalex-snapshot
One-Time Tables for Two-Party Computation
inferredcites →https://doi.org/10.1007/s00440-015-0675-zopenalex-snapshot
High dimensional robust M-estimation: asymptotic variance via approximate message passing
inferredcites →https://doi.org/10.1093/imaiai/iaw013openalex-snapshot
On the optimality of averaging in distributed statistical learning
inferredcites →https://doi.org/10.1109/sp.2013.30openalex-snapshot
Privacy-Preserving Ridge Regression on Hundreds of Millions of Records
inferredcites →https://doi.org/10.1111/j.1365-2362.2011.02527.xopenalex-snapshot
On the linearity of nature or the risk of extending regression lines beyond the observed data
inferredcites →https://doi.org/10.1136/amiajnl-2011-000735openalex-snapshot
A secure distributed logistic regression protocol for the detection of rare adverse drug events
inferredcites →https://doi.org/10.1137/1.9781611972740.21openalex-snapshot
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification
inferredcites →https://doi.org/10.1145/2382196.2382279openalex-snapshot
Foundations of garbled circuits
inferredcites →https://doi.org/10.1145/2808769.2808774openalex-snapshot
Fast, Privacy Preserving Linear Regression over Distributed Datasets based on Pre-Distributed Data
inferredcites →https://doi.org/10.1186/1477-5751-5-5openalex-snapshot
Genetic polymorphisms and susceptibility to lung disease
inferredcites →https://doi.org/10.1186/s40246-018-0147-5openalex-snapshot
The development of large-scale de-identified biomedical databases in the age of genomics—principles and challenges
inferredcites →https://doi.org/10.1198/106186005x47714openalex-snapshot
Secure Regression on Distributed Databases
inferredcites →https://doi.org/10.1214/009053604000000238openalex-snapshot
Optimal predictive model selection
inferredcites →https://doi.org/10.29012/jpc.v1i1.566openalex-snapshot
Secure Multiparty Computation for Privacy-Preserving Data Mining
inferredcites →https://doi.org/10.3150/14-bej645openalex-snapshot
Geometric median and robust estimation in Banach spaces
inferredcites →https://doi.org/10.3390/econometrics4040048openalex-snapshot
Higher Order Bias Correcting Moment Equation for M-Estimation and Its Higher Order Efficiency
inferredcites →https://doi.org/10.48550/arxiv.1305.5029openalex-snapshot
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
inferredcites →https://doi.org/10.5555/2870564.2870566openalex-snapshot
Privacy Preserving Linear Regression on Distributed Databases
inferredcites →https://doi.org/10.5860/choice.34-6323openalex-snapshot
Applied regression analysis, linear models, and related methods
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-53187-4_20openalex-snapshot
Secure Linear Regression Algorithms: A Comparison
inferred← citeshttps://doi.org/10.1007/978-3-030-87094-2_21openalex-snapshot
Decentralised and Privacy Preserving Machine Learning for Multiple Distributed Data Resources
inferred← citeshttps://doi.org/10.1007/978-3-031-55568-8_12openalex-snapshot
Nonlinear Model Combination Approach to Decentralised and Privacy-Preserving Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-61140-7_28openalex-snapshot
Comparison of an Accelerated Garble Embedding Methodology for Privacy Preserving in Biomedical Data Analytics
inferred← citeshttps://doi.org/10.1007/978-3-031-70890-9_18openalex-snapshot
BMI: Bounded Mutual Information for Efficient Privacy-Preserving Feature Selection
inferred← citeshttps://doi.org/10.1007/s00259-021-05339-7openalex-snapshot
Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI
inferred← citeshttps://doi.org/10.1007/s10916-022-01851-xopenalex-snapshot
New Approach to Privacy-Preserving Clinical Decision Support Systems for HIV Treatment
inferred← citeshttps://doi.org/10.1007/s10957-026-02961-zopenalex-snapshot
Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation
inferred← citeshttps://doi.org/10.1007/s12021-021-09525-8openalex-snapshot
NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data
inferred← citeshttps://doi.org/10.1016/j.csbj.2019.03.010openalex-snapshot
Informed Consent in Biomedical Research
inferred← citeshttps://doi.org/10.1016/j.csbj.2025.06.009openalex-snapshot
Revolutionizing healthcare data analytics with federated learning: A comprehensive survey of applications, systems, and future directions
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107399openalex-snapshot
Differential privacy scheme using Laplace mechanism and statistical method computation in deep neural network for privacy preservation
inferred← citeshttps://doi.org/10.1038/s42256-022-00601-5openalex-snapshot
Federated machine learning in data-protection-compliant research
inferred← citeshttps://doi.org/10.1038/s43588-021-00047-6openalex-snapshot
Data privacy through participant empowerment
inferred← citeshttps://doi.org/10.1055/s-0041-1740630openalex-snapshot
Privacy-Preserving Artificial Intelligence Techniques in Biomedicine
inferred← citeshttps://doi.org/10.1109/asonam55673.2022.10068615openalex-snapshot
Using Synthetic Data to Reduce Model Convergence Time in Federated Learning
inferred← citeshttps://doi.org/10.1109/educon54358.2023.10125139openalex-snapshot
AI in Education: Improving Quality for Both Centralized and Decentralized Frameworks
inferred← citeshttps://doi.org/10.1109/uemcon51285.2020.9298174openalex-snapshot
Central versus Distributed Statistical Computing Algorithms-A Comparison
inferred← citeshttps://doi.org/10.1109/uemcon53757.2021.9666559openalex-snapshot
Privacy-Preserving ID3 Algorithms: A Comparison
inferred← citeshttps://doi.org/10.1186/s12859-022-05044-8openalex-snapshot
EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation
inferred← citeshttps://doi.org/10.1186/s12911-020-1041-3openalex-snapshot
A comprehensive tool for creating and evaluating privacy-preserving biomedical prediction models
inferred← citeshttps://doi.org/10.2174/1381612827999210112204732openalex-snapshot
Data Sharing and Privacy in Pharmaceutical Studies
inferred← citeshttps://doi.org/10.2196/18910openalex-snapshot
Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
inferred← citeshttps://doi.org/10.3389/fpsyg.2022.943198openalex-snapshot
A comparison of distributed machine learning methods for the support of “many labs” collaborations in computational modeling of decision making
inferred← citeshttps://doi.org/10.46243/jst.2022.v7.i010.pp163-174openalex-snapshot
PMDP: A Secure Multiparty Computation Framework for Maintaining Multiparty Data Privacy in Cloud Computing
inferred← citeshttps://doi.org/10.48550/arxiv.2103.12271openalex-snapshot
Quantum Secure Multi-party Summation Based on entanglement swapping
inferred← citeshttps://doi.org/10.6084/m9.figshare.26552593openalex-snapshot
Additional file 1 of EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation
inferred← citeshttps://doi.org/10.6084/m9.figshare.26552596openalex-snapshot
Additional file 2 of EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation
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