Database processes must be cache-efficient to effectively utilize modern hardware. In this paper, we analyze the importance of temporal locality and the resultant cache behavior ...
We address performance issues associated with simulationbased algorithms for optimizing Markov reward processes. Specifically, we are concerned with algorithms that exploit the re...
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
In this paper we provide an adaptive modulation approach that uses adaptive pilot symbols which both pilot spacing and power allocation on pilot symbols are optimized in single in...
Personalization systems based upon users' surfing behavior analysis imply three phases: data collection, pattern discovery and recommendation. Due to the dimension of log file...