John Stephan

According to our database1, John Stephan authored at least 15 papers between 2003 and 2024.

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Bibliography

2024
Overcoming the Challenges of Batch Normalization in Federated Learning.
CoRR, 2024

Boosting Robustness by Clipping Gradients in Distributed Learning.
CoRR, 2024

2023
Can Machines Learn Robustly, Privately, and Efficiently?
CoRR, 2023

Practical Homomorphic Aggregation for Byzantine ML.
CoRR, 2023

Distributed Learning with Curious and Adversarial Machines.
CoRR, 2023

Robust Collaborative Learning with Linear Gradient Overhead.
Proceedings of the International Conference on Machine Learning, 2023

On the Privacy-Robustness-Utility Trilemma in Distributed Learning.
Proceedings of the International Conference on Machine Learning, 2023

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
On the Impossible Safety of Large AI Models.
CoRR, 2022

Making Byzantine Decentralized Learning Efficient.
CoRR, 2022

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums.
Proceedings of the International Conference on Machine Learning, 2022

2021
Combining Differential Privacy and Byzantine Resilience in Distributed SGD.
CoRR, 2021

Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?
Proceedings of the PODC '21: ACM Symposium on Principles of Distributed Computing, 2021

2019
HideMyApp: Hiding the Presence of Sensitive Apps on Android.
Proceedings of the 28th USENIX Security Symposium, 2019

2003
Bringing Managers into Theories of Multimarket Competition: CEOs and the Determinants of Market Entry.
Organ. Sci., 2003


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