Online combinatorial optimization with stochastic decision sets and adversarial losses
arXiv:2604.25269v1 Announce Type: new
Abstract: Most work on sequential learning assumes a fixed set of actions that are available all the time. However, in practice, actions can consist of picking subsets of readings from sensors that may break from …