We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Abstract—In this paper, we describe a receiver based congestion control policy that leverages TCP flow control mechanisms to prioritize mixed traffic loads across access links....
Neil T. Spring, Maureen Chesire, Mark Berryman, Vi...
Today's extensible operating systems allow applications to modify kernel behavior by providing mechanisms for application code to run in the kernel address space. The advanta...
Margo I. Seltzer, Yasuhiro Endo, Christopher Small...
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...