Beyond federated learning: On confidentiality-critical machine learning applications in industry

Author:

Zellinger Werner,Wieser Volkmar,Kumar Mohit,Brunner David,Shepeleva Natalia,Gálvez Rafa,Langer Josef,Fischer Lukas,Moser Bernhard

Publisher

Elsevier BV

Subject

General Engineering

Reference47 articles.

1. Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov. How to backdoor federated learning. In Silvia Chiappa and Roberto Calandra, editors, Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, volume 108 of Proceedings of Machine Learning Research, pages 2938-2948, Online, 26-28 Aug 2020. PMLR.

2. Borja Balle and Yu-Xiang Wang. Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising. CoRR, abs/1805.06530, 2018.

3. A theory of learning from different domains;Ben-David;Machine learning,2010

4. Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, and Seraphin Calo. Analyzing federated learning through an adversarial lens. In Kamalika Chaudhuri and Ruslan Salakhutdinov, editors, Proceedings of the 36th International Conference on Machine Learning, volume 97 of Proceedings of Machine Learning Research, pages 634-643, Long Beach, California, USA, 09-15 Jun 2019. PMLR.

5. Pattern recognition and machine learning;Bishop,2006

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