Queueing systems are widely applicable stochastic models with use cases ...
Ensuring that refugees and asylum seekers thrive (e.g., find employment)...
We study Stackelberg games where a principal repeatedly interacts with a...
We study decentralized multi-agent learning in bipartite queuing systems...
Thompson sampling and other Bayesian sequential decision-making algorith...
We study a pricing problem where a seller has k identical copies of a
pr...
We propose an algorithm for tabular episodic reinforcement learning with...
We study "adversarial scaling", a multi-armed bandit model where rewards...
Standard game-theoretic formulations for settings like contextual pricin...
We initiate the study of multi-stage episodic reinforcement learning und...
We study methods for improving fairness to subgroups in settings with
ov...
We study the stochastic multi-armed bandit problem with the graph-based
...
We study the interplay between sequential decision making and avoiding
d...
We introduce a new model of stochastic bandits with adversarial corrupti...
Traditional online algorithms encapsulate decision making under uncertai...
We consider the problem of adversarial (non-stochastic) online learning ...