Optimized opportunistic multicast scheduling (OMS) has been studied previously by the authors for homogeneous cellular networks, where the problem of efficiently transmitting a co...
Tze-Ping Low, Man-On Pun, Yao-Win Peter Hong, C.-C...
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...
Thomas Melluish, Craig Saunders, Ilia Nouretdinov,...
Full revelation of private values is impractical in many large-scale markets, where posted price mechanisms are a simpler alternative. In this work, we compare the asymptotic beha...
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Performing QoS (Quality of Service) control in large computing systems requires an on line metric that is representative of the real state of the system. The Tardiness Quantile Me...
Luciano Bertini, Julius C. B. Leite, Daniel Moss&e...