Data replication is an excellent technique to move and cache data close to users. By replication, data access performance can be improved dramatically. One of the challenges in da...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
In this paper, we propose a new architecture-level parameterized transient thermal behavioral modeling algorithm for emerging thermal related design and optimization problems for ...
Duo Li, Sheldon X.-D. Tan, Eduardo H. Pacheco, Mur...
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
We introduce and analyze a deterministic fluid model that serves as an approximation for the Gt/GI/st + GI manyserver queueing model, which has a general time-varying arrival pro...