| 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 | 70 | 2021 |
| 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 | 32 | 2022 |
| 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 | 27 | 2021 |
| 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 | 20 | 2022 |
| 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 | 3 | 2020 |
| 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 | 3 | 2019 |
| Cross-Silo Training of Differentially Private Models with Secure Multiparty Computation S Pentyala, D Railsback, RJM Maia, D Melanson, R Dowsley, ... | | |
Rafael DowsleyMonash UniversityVerified email at monash.edu
