Abstract-- This paper presents an efficient implementation for correlation based stereo. Research in this area can roughly be divided in two classes: improving accuracy regardless ...
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
We present a QoS management framework that enables us to quantitatively measure QoS, and to analytically plan and allocate resources. In this model, end users' quality prefer...
Chen Lee, John P. Lehoczky, Ragunathan Rajkumar, D...