We investigate a variant of the on-line learning model for classes
of {0,1}-valued functions (concepts) in which the labels of a certain
amount of the input instances are corrupted by adversarial noise.
We propose an extension of a general learning strategy, known as
"Closure Algorithm", to this noise ... more >>>

In the multi-armed bandit problem, a gambler must decide which arm
of K non-identical slot machines to play in a sequence of trials
so as to maximize his reward.
This classical problem has received much attention because of the
simple model it provides of the trade-off between
exploration ... more >>>