Antoine Scheid — accepted AI-conference papers

2024

Incentivized Learning in Principal-Agent Bandit Games

Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, Eric Moulines, Michael Jordan +2

ICML 2024poster

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 misaligned objectives and the choice of action is only left to the agent. However, the principal can influence the agent's decisi…

Cited by 7 Source ↗PDF ↗Scholar ↗

2024

Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality

Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael Jordan, Alain Oliviero Durmus

NeurIPS 2024spotlight

In Economics, the concept of externality refers to any indirect effect resulting from an interaction between players and affecting a third party without compensation. Most of the models within which externality has been studied assume that agents have perfect knowledge of their environment and prefe…

Cited by 2 Source ↗PDF ↗Scholar ↗

2024

Unravelling in Collaborative Learning

Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael Jordan, El-Mahdi El-Mhamdi +1

NeurIPS 2024poster

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 strategic agents who wish to train a model together but have sampling distributions of different quality. The collabora…

Cited by 1 Source ↗PDF ↗Scholar ↗