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...
We consider dense wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector ...
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
Application-specific system-on-chip platforms create the opportunity to customize the cache configuration for optimal performance with minimal chip estate. Simulation, in partic...
In this paper, we show the feasibility of real-time flow monitoring with controllable accuracy in today’s IP networks. Our approach is based on Netflow and A-GAP. A-GAP is a prot...