Sadegh Farhadkhani

According to our database, Sadegh Farhadkhani authored at least 16 papers between 2020 and 2024.

Collaborative distances:

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

2024

On the Relevance of Byzantine Robust Optimization Against Data Poisoning.

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot

CoRR, 2024

Tackling Byzantine Clients in Federated Learning.

Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych

CoRR, 2024

Brief Announcement: A Case for Byzantine Machine Learning.

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot

Proceedings of the 43rd ACM Symposium on Principles of Distributed Computing, 2024

Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates.

Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons.

Julien Fageot, Sadegh Farhadkhani, Lê-Nguyên Hoang, Oscar Villemaud

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication.

Martijn de Vos, Sadegh Farhadkhani, Rachid Guerraoui, Anne-Marie Kermarrec, Rafael Pires, Rishi Sharma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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 Strategyproofness of the Geometric Median.

El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Lê-Nguyên Hoang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

An Equivalence Between Data Poisoning and Byzantine Gradient Attacks.

Sadegh Farhadkhani, Rachid Guerraoui, Lê Nguyên Hoang, Oscar Villemaud

Proceedings of the International Conference on Machine Learning, 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

Strategyproof Learning: Building Trustworthy User-Generated Datasets.

Sadegh Farhadkhani, Rachid Guerraoui, Lê-Nguyên Hoang

CoRR, 2021

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning).

El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Arsany Guirguis, Lê-Nguyên Hoang, Sébastien Rouault

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Collaborative Learning as an Agreement Problem.

El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Arsany Guirguis, Lê Nguyên Hoang, Sébastien Rouault

CoRR, 2020