Sébastien Rouault
3 papers in the PaperMetrix corpus
Papers by this author
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Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?
2021 · arXiv (Cornell University)
This paper addresses the problem of combining Byzantine resilience with privacy in machine learning (ML). Specifically, we study if a distributed implementation of the renowned Stochastic Gradient Descent (SGD) learning algorithm is feasible with both …
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Combining Differential Privacy and Byzantine Resilience in Distributed\n SGD
2021 · arXiv (Cornell University)
Privacy and Byzantine resilience (BR) are two crucial requirements of\nmodern-day distributed machine learning. The two concepts have been extensively\nstudied individually but the question of how to combine them effectively\nremains unanswered. This paper contributes to addressing …
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On Monotonicity in AI Alignment
2025 · arXiv (Cornell University)
Comparison-based preference learning has become central to the alignment of AI models with human preferences. However, these methods may behave counterintuitively. After empirically observing that, when accounting for a preference for response $y$ over $z$, …