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Davis Railsback
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High performance logistic regression for privacy-preserving genome analysis
M De Cock, R Dowsley, ACA Nascimento, D Railsback, J Shen, A Todoki
BMC Medical Genomics 14, 1-18, 2021
622021
Privacy-preserving training of tree ensembles over continuous data
S Adams, C Choudhary, M De Cock, R Dowsley, D Melanson, ...
arXiv preprint arXiv:2106.02769, 2021
212021
Fast privacy-preserving text classification based on secure multiparty computation
A Resende, D Railsback, R Dowsley, ACA Nascimento, DF Aranha
IEEE Transactions on Information Forensics and Security 17, 428-442, 2022
192022
Training differentially private models with secure multiparty computation
S Pentyala, D Railsback, R Maia, R Dowsley, D Melanson, A Nascimento, ...
arXiv preprint arXiv:2202.02625, 2022
132022
Secure training of extra trees classifiers over continuous data
C Choudhary, M De Cock, R Dowsley, A Nascimento, D Railsback
AAAI-20 Workshop on Privacy-Preserving Artificial Intelligence, 2020
32020
Fast secure logistic regression for high dimensional gene data
M De Cock, R Dowsley, A Nascimento, D Railsback, J Shen, A Todoki
Privacy in machine learning (PriML2019). Workshop at NeurIPS, 1-7, 2019
32019
Cross-Silo Training of Differentially Private Models with Secure Multiparty Computation
S Pentyala, D Railsback, RJM Maia, D Melanson, R Dowsley, ...
2022
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Articles 1–7