Helen: Maliciously secure coopetitive learning for linear models

W Zheng, RA Popa, JE Gonzalez… - 2019 IEEE symposium …, 2019 - ieeexplore.ieee.org
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …
被引用次数：178 相关文章

Helen: Maliciously Secure Coopetitive Learning for Linear Models

W Zheng, RA Popa, JE Gonzalez, I Stoica - arXiv preprint arXiv …, 2019 - arxiv.org
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …
[PDF] berkeley.edu

[PDF][PDF] Helen: Maliciously Secure Coopetitive Learning for Linear Models

W Zheng, RA Popa, JE Gonzalez, I Stoica - people.eecs.berkeley.edu
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …

Helen: Maliciously Secure Coopetitive Learning for Linear Models

W Zheng, RA Popa, JE Gonzalez, I Stoica - arXiv e-prints, 2019 - ui.adsabs.harvard.edu
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …
[PDF] github.io

[PDF][PDF] Helen: Maliciously Secure Coopetitive Learning for Linear Models

W Zheng, RA Popa, JE Gonzalez, I Stoica - wzheng.github.io
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …

Helen: Maliciously Secure Coopetitive Learning for Linear Models

W Zheng, RA Popa, JE Gonzalez… - 2019 IEEE Symposium on …, 2019 - computer.org
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …
[PDF] berkeley.edu

[PDF][PDF] Helen: Maliciously Secure Coopetitive Learning for Linear Models

W Zheng, RA Popa, JE Gonzalez, I Stoica - people.eecs.berkeley.edu
Many organizations wish to collaboratively train machine learning models on their combined
datasets for a common benefit (eg, better medical research, or fraud detection). However …