15 citations · 47 across the 20 of their papers we have counts for
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stat.ML2026★ 1 cited
Byzantine Machine Learning: MultiKrum and an optimal notion of robustness
Gilles Bareilles, Wassim Bouaziz, Julien Fageot +1
Aggregation rules are the cornerstone of distributed (or federated) learning in the presence of adversaries, under the so-called Byzantine threat model. They are also interesting m…
stat.ML2025
The Strong, Weak and Benign Goodhart's law. An independence-free and paradigm-agnostic formalisation
Adrien Majka, El-Mahdi El-Mhamdi
Goodhart's law is a famous adage in policy-making that states that ``When a measure becomes a target, it ceases to be a good measure''. As machine learning models and the optimisat…
stat.ML2024★ 2 cited
On Goodhart's law, with an application to value alignment
El-Mahdi El-Mhamdi, Lê-Nguyên Hoang
``When a measure becomes a target, it ceases to be a good measure'', this adage is known as {\it Goodhart's law}. In this paper, we investigate formally this law and prove that it…