John Stephan

According to our database, John Stephan authored at least 17 papers between 2003 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2025

CrowdProve: Community Proving for ZK Rollups.

John Stephan, Matej Pavlovic, Antonio Locascio, Benjamin Livshits

CoRR, January, 2025

2024

Overcoming the Challenges of Batch Normalization in Federated Learning.

Rachid Guerraoui, Rafael Pinot, Geovani Rizk, John Stephan, François Taïani

CoRR, 2024

Boosting Robustness by Clipping Gradients in Distributed Learning.

Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Ahmed Jellouli, Geovani Rizk, John Stephan

CoRR, 2024

Towards Practical Homomorphic Aggregation in Byzantine-Resilient Distributed Learning.

Antoine Choffrut, Rachid Guerraoui, Rafael Pinot, Renaud Sirdey, John Stephan, Martin Zuber

Proceedings of the 25th International Middleware Conference, 2024

2023

Can Machines Learn Robustly, Privately, and Efficiently?

Youssef Allouah, Rachid Guerraoui, John Stephan

CoRR, 2023

Practical Homomorphic Aggregation for Byzantine ML.

Antoine Choffrut, Rachid Guerraoui, Rafael Pinot, Renaud Sirdey, John Stephan, Martin Zuber

CoRR, 2023

Distributed Learning with Curious and Adversarial Machines.

Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan

CoRR, 2023

Robust Collaborative Learning with Linear Gradient Overhead.

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan

Proceedings of the International Conference on Machine Learning, 2023

On the Privacy-Robustness-Utility Trilemma in Distributed Learning.

Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan

Proceedings of the International Conference on Machine Learning, 2023

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity.

Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

On the Impossible Safety of Large AI Models.

El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan

CoRR, 2022

Making Byzantine Decentralized Learning Efficient.

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê Nguyên Hoang, Rafael Pinot, John Stephan

CoRR, 2022

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums.

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan

Proceedings of the International Conference on Machine Learning, 2022

2021

Combining Differential Privacy and Byzantine Resilience in Distributed SGD.

Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sébastien Rouault, John Stephan

CoRR, 2021

Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?

Rachid Guerraoui, Nirupam Gupta, Rafaël Pinot, Sébastien Rouault, John Stephan

Proceedings of the PODC '21: ACM Symposium on Principles of Distributed Computing, 2021

2019

HideMyApp: Hiding the Presence of Sensitive Apps on Android.

Anh Pham, Italo Dacosta, Eleonora Losiouk, John Stephan, Kévin Huguenin, Jean-Pierre Hubaux

Proceedings of the 28th USENIX Security Symposium, 2019

2003

Bringing Managers into Theories of Multimarket Competition: CEOs and the Determinants of Market Entry.

John Stephan, Johann Peter Murmann, Warren Boeker, Jerry Goodstein

Organ. Sci., 2003