In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Often, independent organizations define and advocate different XML formats for a similar purpose and, as a result, application programs need to mutually convert between such forma...
In this paper we study a dynamic version of capacity maximization in the physical model of wireless communication. In our model, requests for connections between pairs of points i...
Sigma, the first single-round group membership (GM) algorithm, was recently introduced and demonstrated to operate consistently with theoretical expectations in a simulated WAN en...
Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast ...