Jun 1, 2022 · Abstract:Consider a bandit algorithm that recommends actions to self-interested users in a recommendation system.
Consider a bandit algorithm that recommends actions to self-interested users in a recommendation system. The users are free to choose other actions and need.
Oct 31, 2022 · This paper investigates the problem of incentivized exploration in the combinatorial semi-bandits setting. The reviewers are overall positive ...
Jun 1, 2022 · We focus on a paradigmatic exploration problem with structure: combinatorial semi-bandits. We prove that Thompson Sampling, when applied to.
Topics · Incentivized Exploration · Combinatorial Semi-Bandits · Recommendation Systems · Bandit Algorithms · Incentive Compatible · Thompson Sampling ...
This was generalized to the combinato- rial semibandit in (Hu et al., 2022). We give an analog of this result for linear bandits, where the independence of the ...
We consider incentivized exploration: a version of multi-armed bandits where the choice of arms is controlled by self-interested agents, and the algorithm can ...
Consider a bandit algorithm that recommends actions to self-interested users in a recommendation system. The users are free to choose other actions and need ...
This was generalized to the combinatorial semibandit in Hu-Ngo-Slivkins-Wu (NeurIPS 2022). We give an analog of this result for linear bandits, where the ...
Jul 23, 2023 · This was generalized to the combinatorial semibandit in (Hu et al., 2022). We give an analog of this result for linear bandits, where the ...