Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
A scalable podcast solution developed at the University of Washington makes the podcasting of class lectures easy for faculty by automating the capture, uploading, and delivery of...
In this paper the Northrhine-Westphalian metacomputing initiative is described. We start by discussing various general aspects of metacomputing and explain the reasons for founding...
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
—Network protocols have traditionally been designed using a layered method in part because it is easier to implement some portions of network protocols in software and other port...
Dola Saha, Aveek Dutta, Dirk Grunwald, Douglas C. ...