We consider the problem of minimizing a convex function over a closed co...
We consider contextual bandit problems with knapsacks [CBwK], a problem ...
We lay the foundations of a non-parametric theory of best-arm identifica...
We consider contextual bandits with knapsacks, with an underlying struct...
We provide a setting and a general approach to fair online learning with...
We consider the bandit-based framework for diversity-preserving
recommen...
We consider stochastic bandit problems with K arms, each associated with...
We revisit the interest of classical statistical techniques for sales
fo...
We propose a contextual-bandit approach for demand side management by
of...
We consider the setting of online linear regression for arbitrary
determ...
In the context of K-armed stochastic bandits with distribution only assu...
We study online aggregation of the predictions of experts, and first sho...
In the standard setting of approachability there are two players and a t...
In approachability with full monitoring there are two types of condition...
We consider the setting of sequential prediction of arbitrary sequences ...
Mirror descent with an entropic regularizer is known to achieve shifting...
We provide yet another proof of the existence of calibrated forecasters;...