3 papers
stat.ML2026
The Sampling Complexity of Condorcet Winner Identification in Dueling Bandits
El Mehdi Saad, Victor Thuot, Nicolas Verzelen
We study best-arm identification in stochastic dueling bandits under the sole assumption that a Condorcet winner exists, i.e., an arm that wins each noisy pairwise comparison with…
stat.ML2026
Nonparametric Kernel Clustering with Bandit Feedback
Victor Thuot, Sebastian Vogt, Debarghya Ghoshdastidar +1
Clustering with bandit feedback refers to the problem of partitioning a set of items, where the clustering algorithm can sequentially query the items to receive noisy observations.…
stat.ML2025
Clustering Items through Bandit Feedback: Finding the Right Feature out of Many
Maximilian Graf, Victor Thuot, Nicolas Verzelen
We study the problem of clustering a set of items based on bandit feedback. Each of the items is characterized by a feature vector, with a possibly large dimension . The ite…