Rapid increases in computing and communication performance are exacerbating the long-standing problem of performance-limited input/output. Indeed, for many otherwise scalable para...
Phyllis Crandall, Ruth A. Aydt, Andrew A. Chien, D...
Abstract: Modern software development approaches, especially the model-driven approaches, heavily rely on the use of models during the whole development process. With the increasin...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
While the virtual memory management in Linux 2.2 has decent performance for many workloads, it suffers from a number of problems. The first part of this paper contains a descripti...
In our previous work (`An Algebraic Watchdog for Wireless Network Coding'), we proposed a new scheme in which nodes can detect malicious behaviors probabilistically, police th...