36 citations · 36 across the 2 of their papers we have counts for
3 papers
cs.LG2020
Better Boosting with Bandits for Online Learning
Nikolaos Nikolaou, Joseph Mellor, Nikunj C. Oza +1
Probability estimates generated by boosting ensembles are poorly calibrated because of the margin maximization nature of the algorithm. The outputs of the ensemble need to be prope…
cs.LG2018
The K-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates
Henry WJ Reeve, Joe Mellor, Gavin Brown
In this paper we propose and explore the k-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates. We focus on a setting where the covariates are supported on a me…
cs.LG2013★ 36 cited
Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection
Joseph Mellor, Jonathan Shapiro
Thompson Sampling has recently been shown to be optimal in the Bernoulli Multi-Armed Bandit setting[Kaufmann et al., 2012]. This bandit problem assumes stationary distributions for…