1 citations · 1 across the 10 of their papers we have counts for
10 papers
Test-then-Punish: A Statistical Approach to Repeated Games
Aymeric Capitaine, Antoine Scheid, Etienne Boursier +2
We study discounted infinitely repeated games in which players agree on a cooperative mixed action profile but, at each step, observe only the realized pure actions. This form of i…
Softmax as Linear Attention in the Large-Prompt Regime: a Measure-based Perspective
Etienne Boursier, Claire Boyer
Softmax attention is a central component of transformer architectures, yet its nonlinear structure poses significant challenges for theoretical analysis. We develop a unified, meas…
Online Decision-Focused Learning
Aymeric Capitaine, Maxime Haddouche, Eric Moulines +3
Decision-focused learning (DFL) is an increasingly popular paradigm for training predictive models whose outputs are used in decision-making tasks. Instead of merely optimizing for…
Online Decision-Making in Tree-Like Multi-Agent Games with Transfers
Antoine Scheid, Etienne Boursier, Alain Durmus +2
The widespread deployment of Machine Learning systems everywhere raises challenges, such as dealing with interactions or competition between multiple learners. In that goal, we stu…
Prediction-Aware Learning in Multi-Agent Systems
Aymeric Capitaine, Etienne Boursier, Eric Moulines +2
The framework of uncoupled online learning in multiplayer games has made significant progress in recent years. In particular, the development of time-varying games has considerably…
Optimal Design for Reward Modeling in RLHF
Antoine Scheid, Etienne Boursier, Alain Durmus +4
Reinforcement Learning from Human Feedback (RLHF) has become a popular approach to align language models (LMs) with human preferences. This method involves collecting a large datas…
Unravelling in Collaborative Learning
Aymeric Capitaine, Etienne Boursier, Antoine Scheid +4
Collaborative learning offers a promising avenue for leveraging decentralized data. However, collaboration in groups of strategic learners is not a given. In this work, we consider…
Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality
Antoine Scheid, Aymeric Capitaine, Etienne Boursier +3
In economic theory, the concept of externality refers to any indirect effect resulting from an interaction between players that affects the social welfare. Most of the models withi…
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier +5
This work considers a repeated principal-agent bandit game, where the principal can only interact with her environment through the agent. The principal and the agent have misaligne…
Approximate information maximization for bandit games
Alex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson +1
Entropy maximization and free energy minimization are general physical principles for modeling the dynamics of various physical systems. Notable examples include modeling decision-…