Efficient Prototype Selection via Multi-Armed Bandits. (arXiv:2210.01860v1 [cs.LG])

In this work, we propose a multi-armed bandit based framework for identifying
a compact set of informative data instances (i.e., the prototypes) that best
represents a given target set. Prototypical examples of a given dataset offer
interpretable insights into the underlying data distribution and assist in
example-based reasoning, thereby influencing every sphere of human decision
making. A key challenge is the large-scale setting, in which similarity
comparison between pairs of data points needs to be done for almost all
possible …

arxiv multi-armed bandits