23 citations · 26 across the 3 of their papers we have counts for
4 papers
On Monotonicity in AI Alignment
Gilles Bareilles, Julien Fageot, Lê-Nguyên Hoang +4
Comparison-based preference learning has become central to the alignment of AI models with human preferences. However, these methods may behave counterintuitively. After empiricall…
Generalizing while preserving monotonicity in comparison-based preference learning models
Julien Fageot, Peva Blanchard, Gilles Bareilles +1
If you tell a learning model that you prefer an alternative over another alternative , then you probably expect the model to be monotone, that is, the valuation of incre…
Byzantine-Tolerant Machine Learning
Peva Blanchard, El Mahdi El Mhamdi, Rachid Guerraoui +1
The growth of data, the need for scalability and the complexity of models used in modern machine learning calls for distributed implementations. Yet, as of today, distributed machi…
Self-Stabilizing Paxos
Peva Blanchard, Shlomi Dolev, Joffroy Beauquier +1
We present the first self-stabilizing consensus and replicated state machine for asynchronous message passing systems. The scheme does not require that all participants make a cert…