Due to numerous applications in retail and (online) advertising the prob...
In a recent work, Laforgue et al. introduce the model of last switch
dep...
We consider Pareto front identification for linear bandits (PFILin) wher...
We consider the linear contextual multi-class multi-period packing
probl...
We consider a stochastic multi-armed bandit (MAB) problem motivated by
“...
We study the problem of allocating T sequentially arriving items among n...
We consider a bandit problem with countably many arms, partitioned into
...
One of the key drivers of complexity in the classical (stochastic)
multi...
We consider a stochastic bandit problem with countably many arms that be...
We consider a novel formulation of the dynamic pricing and demand learni...
We consider a discounted infinite horizon optimal stopping problem. If t...
We study problem-dependent rates, i.e., generalization errors that scale...
We consider a stochastic contextual bandit problem where the dimension d...
The principle of optimism in the face of uncertainty is one of the most
...
We consider the problem of designing an adaptive sequence of questions t...
In this paper we develop a unified approach for solving a wide class of
...
Different risk-related criteria have received recent interest in learnin...
In a multi-armed bandit (MAB) problem a gambler needs to choose at each ...