3 papers
stat.ML2026
Spectral bandits
Tomáš Kocák, Rémi Munos, Branislav Kveton +2
Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs of arms are smooth on a graph.…
cs.LG2026
Spectral Thompson sampling
Tomas Kocak, Michal Valko, Remi Munos +1
Thompson Sampling (TS) has attracted a lot of interest due to its good empirical performance, in particular in the computational advertising. Though successful, the tools for its p…
cs.GT2024
Dynamic Pricing and Advertising with Demand Learning
Shipra Agrawal, Yiding Feng, Wei Tang
We consider a novel pricing and advertising framework in which a seller not only sets the product price but also designs flexible advertising schemes to influence customers' valuat…