In modern digital ICs, the increasing demand for performance and throughput requires operating frequencies of hundreds of megahertz, and in several cases exceeding the gigahertz r...
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...
Xi Chen, Jingrui He, Rick Lawrence, Jaime G. Carbo...
Most earlier studies of DHTs under churn have either depended on simulations as the primary investigation tool, or on establishing bounds for DHTs to function. In this paper, we pr...
Supriya Krishnamurthy, Sameh El-Ansary, Erik Aurel...
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...